re-structure Java API, add Scala API and consolidate the names of Java/Scala API
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CodingCat
parent
fc4c88fceb
commit
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9
.gitignore
vendored
9
.gitignore
vendored
@ -70,3 +70,12 @@ config.mk
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xgboost
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*.data
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build_plugin
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dmlc-core
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.idea
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recommonmark/
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tags
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*.iml
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*.class
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target
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*.swp
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5
Makefile
5
Makefile
@ -84,7 +84,7 @@ $(DMLC_CORE)/libdmlc.a:
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$(RABIT)/lib/$(LIB_RABIT):
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+ cd $(RABIT); make lib/$(LIB_RABIT); cd $(ROOTDIR)
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java: java/libxgboost4j.so
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jvm-packages: jvm-packages/lib/libxgboost4j.so
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SRC = $(wildcard src/*.cc src/*/*.cc)
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ALL_OBJ = $(patsubst src/%.cc, build/%.o, $(SRC)) $(PLUGIN_OBJS)
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@ -120,7 +120,8 @@ lib/libxgboost.dll lib/libxgboost.so: $(ALL_DEP)
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@mkdir -p $(@D)
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$(CXX) $(CFLAGS) -shared -o $@ $(filter %.o %a, $^) $(LDFLAGS)
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java/libxgboost4j.so: java/xgboost4j_wrapper.cpp $(ALL_DEP)
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jvm-packages/lib/libxgboost4j.so: jvm-packages/xgboost4j/src/native/xgboost4j.cpp $(ALL_DEP)
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@mkdir -p $(@D)
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$(CXX) $(CFLAGS) $(JAVAINCFLAGS) -shared -o $@ $(filter %.cpp %.o %.a, $^) $(LDFLAGS)
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xgboost: $(CLI_OBJ) $(ALL_DEP)
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@ -1,36 +0,0 @@
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<?xml version="1.0" encoding="UTF-8"?>
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<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
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<modelVersion>4.0.0</modelVersion>
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<groupId>org.dmlc</groupId>
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<artifactId>xgboost4j-demo</artifactId>
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<version>1.0</version>
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<packaging>jar</packaging>
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<properties>
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<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
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<maven.compiler.source>1.7</maven.compiler.source>
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<maven.compiler.target>1.7</maven.compiler.target>
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</properties>
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<dependencies>
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<dependency>
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<groupId>org.dmlc</groupId>
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<artifactId>xgboost4j</artifactId>
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<version>1.1</version>
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</dependency>
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<dependency>
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<groupId>commons-io</groupId>
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<artifactId>commons-io</artifactId>
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<version>2.4</version>
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</dependency>
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<dependency>
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<groupId>org.apache.commons</groupId>
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<artifactId>commons-lang3</artifactId>
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<version>3.4</version>
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</dependency>
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<dependency>
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<groupId>junit</groupId>
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<artifactId>junit</artifactId>
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<version>4.11</version>
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<scope>test</scope>
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</dependency>
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</dependencies>
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</project>
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@ -1,164 +0,0 @@
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/*
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Copyright (c) 2014 by Contributors
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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*/
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package org.dmlc.xgboost4j.demo;
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import java.io.File;
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import java.io.IOException;
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import java.io.UnsupportedEncodingException;
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import java.util.AbstractMap;
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import java.util.AbstractMap.SimpleEntry;
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import java.util.ArrayList;
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import java.util.Arrays;
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import java.util.HashMap;
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import java.util.List;
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import java.util.Map;
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import java.util.Map.Entry;
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import org.dmlc.xgboost4j.Booster;
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import org.dmlc.xgboost4j.DMatrix;
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import org.dmlc.xgboost4j.demo.util.DataLoader;
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import org.dmlc.xgboost4j.demo.util.Params;
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import org.dmlc.xgboost4j.util.Trainer;
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import org.dmlc.xgboost4j.util.XGBoostError;
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/**
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* a simple example of java wrapper for xgboost
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* @author hzx
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*/
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public class BasicWalkThrough {
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public static boolean checkPredicts(float[][] fPredicts, float[][] sPredicts) {
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if(fPredicts.length != sPredicts.length) {
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return false;
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}
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for(int i=0; i<fPredicts.length; i++) {
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if(!Arrays.equals(fPredicts[i], sPredicts[i])) {
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return false;
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}
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}
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return true;
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}
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public static void main(String[] args) throws UnsupportedEncodingException, IOException, XGBoostError {
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// load file from text file, also binary buffer generated by xgboost4j
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DMatrix trainMat = new DMatrix("../../demo/data/agaricus.txt.train");
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DMatrix testMat = new DMatrix("../../demo/data/agaricus.txt.test");
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//specify parameters
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//note: any Iterable<Entry<String, Object>> object would be used as paramters
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//e.g.
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// Map<String, Object> paramMap = new HashMap<String, Object>() {
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// {
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// put("eta", 1.0);
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// put("max_depth", 2);
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// put("silent", 1);
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// put("objective", "binary:logistic");
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// }
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// };
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// Iterable<Entry<String, Object>> param = paramMap.entrySet();
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//or
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// List<Entry<String, Object>> param = new ArrayList<Entry<String, Object>>() {
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// {
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// add(new SimpleEntry<String, Object>("eta", 1.0));
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// add(new SimpleEntry<String, Object>("max_depth", 2.0));
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// add(new SimpleEntry<String, Object>("silent", 1));
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// add(new SimpleEntry<String, Object>("objective", "binary:logistic"));
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// }
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// };
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//we use a util class Params to handle parameters as example
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Iterable<Entry<String, Object>> param = new Params() {
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{
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put("eta", 1.0);
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put("max_depth", 2);
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put("silent", 1);
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put("objective", "binary:logistic");
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}
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};
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//specify watchList to set evaluation dmats
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//note: any Iterable<Entry<String, DMatrix>> object would be used as watchList
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//e.g.
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//an entrySet of Map is good
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// Map<String, DMatrix> watchMap = new HashMap<>();
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// watchMap.put("train", trainMat);
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// watchMap.put("test", testMat);
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// Iterable<Entry<String, DMatrix>> watchs = watchMap.entrySet();
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//we use a List of Entry<String, DMatrix> WatchList as example
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List<Entry<String, DMatrix>> watchs = new ArrayList<>();
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watchs.add(new SimpleEntry<>("train", trainMat));
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watchs.add(new SimpleEntry<>("test", testMat));
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//set round
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int round = 2;
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//train a boost model
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Booster booster = Trainer.train(param, trainMat, round, watchs, null, null);
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//predict
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float[][] predicts = booster.predict(testMat);
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//save model to modelPath
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File file = new File("./model");
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if(!file.exists()) {
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file.mkdirs();
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}
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String modelPath = "./model/xgb.model";
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booster.saveModel(modelPath);
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//dump model
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booster.dumpModel("./model/dump.raw.txt", false);
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//dump model with feature map
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booster.dumpModel("./model/dump.nice.txt", "../../demo/data/featmap.txt", false);
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//save dmatrix into binary buffer
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testMat.saveBinary("./model/dtest.buffer");
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//reload model and data
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Booster booster2 = new Booster(param, "./model/xgb.model");
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DMatrix testMat2 = new DMatrix("./model/dtest.buffer");
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float[][] predicts2 = booster2.predict(testMat2);
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//check the two predicts
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System.out.println(checkPredicts(predicts, predicts2));
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System.out.println("start build dmatrix from csr sparse data ...");
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//build dmatrix from CSR Sparse Matrix
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DataLoader.CSRSparseData spData = DataLoader.loadSVMFile("../../demo/data/agaricus.txt.train");
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DMatrix trainMat2 = new DMatrix(spData.rowHeaders, spData.colIndex, spData.data, DMatrix.SparseType.CSR);
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trainMat2.setLabel(spData.labels);
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//specify watchList
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List<Entry<String, DMatrix>> watchs2 = new ArrayList<>();
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watchs2.add(new SimpleEntry<>("train", trainMat2));
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watchs2.add(new SimpleEntry<>("test", testMat2));
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Booster booster3 = Trainer.train(param, trainMat2, round, watchs2, null, null);
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float[][] predicts3 = booster3.predict(testMat2);
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//check predicts
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System.out.println(checkPredicts(predicts, predicts3));
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}
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}
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@ -1,54 +0,0 @@
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/*
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Copyright (c) 2014 by Contributors
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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*/
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package org.dmlc.xgboost4j.demo;
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import java.io.IOException;
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import org.dmlc.xgboost4j.DMatrix;
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import org.dmlc.xgboost4j.util.Trainer;
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import org.dmlc.xgboost4j.demo.util.Params;
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import org.dmlc.xgboost4j.util.XGBoostError;
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/**
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* an example of cross validation
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* @author hzx
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*/
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public class CrossValidation {
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public static void main(String[] args) throws IOException, XGBoostError {
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//load train mat
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DMatrix trainMat = new DMatrix("../../demo/data/agaricus.txt.train");
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//set params
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Params param = new Params() {
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{
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put("eta", 1.0);
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put("max_depth", 3);
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put("silent", 1);
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put("nthread", 6);
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put("objective", "binary:logistic");
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put("gamma", 1.0);
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put("eval_metric", "error");
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}
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};
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//do 5-fold cross validation
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int round = 2;
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int nfold = 5;
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//set additional eval_metrics
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String[] metrics = null;
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String[] evalHist = Trainer.crossValiation(param, trainMat, round, nfold, metrics, null, null);
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}
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}
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@ -1,54 +0,0 @@
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/*
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Copyright (c) 2014 by Contributors
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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*/
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package org.dmlc.xgboost4j.demo.util;
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import java.util.ArrayList;
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import java.util.Iterator;
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import java.util.List;
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import java.util.Map.Entry;
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import java.util.AbstractMap;
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/**
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* a util class for handle params
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* @author hzx
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*/
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public class Params implements Iterable<Entry<String, Object>>{
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List<Entry<String, Object>> params = new ArrayList<>();
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/**
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* put param key-value pair
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* @param key
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* @param value
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*/
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public void put(String key, Object value) {
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params.add(new AbstractMap.SimpleEntry<>(key, value));
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}
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@Override
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public String toString(){
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String paramsInfo = "";
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for(Entry<String, Object> param : params) {
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paramsInfo += param.getKey() + ":" + param.getValue() + "\n";
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}
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return paramsInfo;
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}
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@Override
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public Iterator<Entry<String, Object>> iterator() {
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return params.iterator();
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}
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}
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@ -1,35 +0,0 @@
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<?xml version="1.0" encoding="UTF-8"?>
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<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
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<modelVersion>4.0.0</modelVersion>
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<groupId>org.dmlc</groupId>
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<artifactId>xgboost4j</artifactId>
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<version>1.1</version>
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<packaging>jar</packaging>
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<properties>
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<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
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<maven.compiler.source>1.7</maven.compiler.source>
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<maven.compiler.target>1.7</maven.compiler.target>
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</properties>
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<reporting>
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<plugins>
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<plugin>
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<groupId>org.apache.maven.plugins</groupId>
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<artifactId>maven-javadoc-plugin</artifactId>
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<version>2.10.3</version>
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</plugin>
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</plugins>
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</reporting>
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<dependencies>
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<dependency>
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<groupId>junit</groupId>
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<artifactId>junit</artifactId>
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<version>4.11</version>
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<scope>test</scope>
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</dependency>
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<dependency>
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<groupId>commons-logging</groupId>
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<artifactId>commons-logging</artifactId>
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<version>1.2</version>
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</dependency>
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</dependencies>
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</project>
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@ -1,484 +0,0 @@
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/*
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Copyright (c) 2014 by Contributors
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Licensed under the Apache License, Version 2.0 (the "License");
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||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
*/
|
||||
package org.dmlc.xgboost4j;
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import java.io.BufferedWriter;
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import java.io.File;
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import java.io.FileNotFoundException;
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import java.io.FileOutputStream;
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import java.io.IOException;
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import java.io.OutputStreamWriter;
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import java.io.UnsupportedEncodingException;
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import java.util.HashMap;
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import java.util.List;
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import java.util.Map;
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import java.util.Map.Entry;
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import org.apache.commons.logging.Log;
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import org.apache.commons.logging.LogFactory;
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import org.dmlc.xgboost4j.util.Initializer;
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import org.dmlc.xgboost4j.util.ErrorHandle;
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import org.dmlc.xgboost4j.util.XGBoostError;
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import org.dmlc.xgboost4j.wrapper.XgboostJNI;
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/**
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* Booster for xgboost, similar to the python wrapper xgboost.py
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* but custom obj function and eval function not supported at present.
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* @author hzx
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*/
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public final class Booster {
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private static final Log logger = LogFactory.getLog(Booster.class);
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long handle = 0;
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//load native library
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static {
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try {
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Initializer.InitXgboost();
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} catch (IOException ex) {
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logger.error("load native library failed.");
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logger.error(ex);
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}
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}
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/**
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* init Booster from dMatrixs
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* @param params parameters
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* @param dMatrixs DMatrix array
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* @throws org.dmlc.xgboost4j.util.XGBoostError native error
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*/
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public Booster(Iterable<Entry<String, Object>> params, DMatrix[] dMatrixs) throws XGBoostError {
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init(dMatrixs);
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setParam("seed","0");
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setParams(params);
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}
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/**
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* load model from modelPath
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* @param params parameters
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* @param modelPath booster modelPath (model generated by booster.saveModel)
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* @throws org.dmlc.xgboost4j.util.XGBoostError native error
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||||
*/
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||||
public Booster(Iterable<Entry<String, Object>> params, String modelPath) throws XGBoostError {
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||||
init(null);
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||||
if(modelPath == null) {
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||||
throw new NullPointerException("modelPath : null");
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||||
}
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||||
loadModel(modelPath);
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||||
setParam("seed","0");
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||||
setParams(params);
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||||
}
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||||
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||||
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|
||||
|
||||
private void init(DMatrix[] dMatrixs) throws XGBoostError {
|
||||
long[] handles = null;
|
||||
if(dMatrixs != null) {
|
||||
handles = dMatrixs2handles(dMatrixs);
|
||||
}
|
||||
long[] out = new long[1];
|
||||
ErrorHandle.checkCall(XgboostJNI.XGBoosterCreate(handles, out));
|
||||
|
||||
handle = out[0];
|
||||
}
|
||||
|
||||
/**
|
||||
* set parameter
|
||||
* @param key param name
|
||||
* @param value param value
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public final void setParam(String key, String value) throws XGBoostError {
|
||||
ErrorHandle.checkCall(XgboostJNI.XGBoosterSetParam(handle, key, value));
|
||||
}
|
||||
|
||||
/**
|
||||
* set parameters
|
||||
* @param params parameters key-value map
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public void setParams(Iterable<Entry<String, Object>> params) throws XGBoostError {
|
||||
if(params!=null) {
|
||||
for(Map.Entry<String, Object> entry : params) {
|
||||
setParam(entry.getKey(), entry.getValue().toString());
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* Update (one iteration)
|
||||
* @param dtrain training data
|
||||
* @param iter current iteration number
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public void update(DMatrix dtrain, int iter) throws XGBoostError {
|
||||
ErrorHandle.checkCall(XgboostJNI.XGBoosterUpdateOneIter(handle, iter, dtrain.getHandle()));
|
||||
}
|
||||
|
||||
/**
|
||||
* update with customize obj func
|
||||
* @param dtrain training data
|
||||
* @param iter current iteration number
|
||||
* @param obj customized objective class
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public void update(DMatrix dtrain, int iter, IObjective obj) throws XGBoostError {
|
||||
float[][] predicts = predict(dtrain, true);
|
||||
List<float[]> gradients = obj.getGradient(predicts, dtrain);
|
||||
boost(dtrain, gradients.get(0), gradients.get(1));
|
||||
}
|
||||
|
||||
/**
|
||||
* update with give grad and hess
|
||||
* @param dtrain training data
|
||||
* @param grad first order of gradient
|
||||
* @param hess seconde order of gradient
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public void boost(DMatrix dtrain, float[] grad, float[] hess) throws XGBoostError {
|
||||
if(grad.length != hess.length) {
|
||||
throw new AssertionError(String.format("grad/hess length mismatch %s / %s", grad.length, hess.length));
|
||||
}
|
||||
ErrorHandle.checkCall(XgboostJNI.XGBoosterBoostOneIter(handle, dtrain.getHandle(), grad, hess));
|
||||
}
|
||||
|
||||
/**
|
||||
* evaluate with given dmatrixs.
|
||||
* @param evalMatrixs dmatrixs for evaluation
|
||||
* @param evalNames name for eval dmatrixs, used for check results
|
||||
* @param iter current eval iteration
|
||||
* @return eval information
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public String evalSet(DMatrix[] evalMatrixs, String[] evalNames, int iter) throws XGBoostError {
|
||||
long[] handles = dMatrixs2handles(evalMatrixs);
|
||||
String[] evalInfo = new String[1];
|
||||
ErrorHandle.checkCall(XgboostJNI.XGBoosterEvalOneIter(handle, iter, handles, evalNames, evalInfo));
|
||||
return evalInfo[0];
|
||||
}
|
||||
|
||||
/**
|
||||
* evaluate with given customized Evaluation class
|
||||
* @param evalMatrixs evaluation matrix
|
||||
* @param evalNames evaluation names
|
||||
* @param iter number of interations
|
||||
* @param eval custom evaluator
|
||||
* @return eval information
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public String evalSet(DMatrix[] evalMatrixs, String[] evalNames, int iter, IEvaluation eval) throws XGBoostError {
|
||||
String evalInfo = "";
|
||||
for(int i=0; i<evalNames.length; i++) {
|
||||
String evalName = evalNames[i];
|
||||
DMatrix evalMat = evalMatrixs[i];
|
||||
float evalResult = eval.eval(predict(evalMat), evalMat);
|
||||
String evalMetric = eval.getMetric();
|
||||
evalInfo += String.format("\t%s-%s:%f", evalName,evalMetric, evalResult);
|
||||
}
|
||||
return evalInfo;
|
||||
}
|
||||
|
||||
/**
|
||||
* evaluate with given dmatrix handles;
|
||||
* @param dHandles evaluation data handles
|
||||
* @param evalNames name for eval dmatrixs, used for check results
|
||||
* @param iter current eval iteration
|
||||
* @return eval information
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public String evalSet(long[] dHandles, String[] evalNames, int iter) throws XGBoostError {
|
||||
String[] evalInfo = new String[1];
|
||||
ErrorHandle.checkCall(XgboostJNI.XGBoosterEvalOneIter(handle, iter, dHandles, evalNames, evalInfo));
|
||||
return evalInfo[0];
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* evaluate with given dmatrix, similar to evalSet
|
||||
* @param evalMat evaluation matrix
|
||||
* @param evalName evaluation name
|
||||
* @param iter number of iterations
|
||||
* @return eval information
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public String eval(DMatrix evalMat, String evalName, int iter) throws XGBoostError {
|
||||
DMatrix[] evalMats = new DMatrix[] {evalMat};
|
||||
String[] evalNames = new String[] {evalName};
|
||||
return evalSet(evalMats, evalNames, iter);
|
||||
}
|
||||
|
||||
/**
|
||||
* base function for Predict
|
||||
* @param data data
|
||||
* @param outPutMargin output margin
|
||||
* @param treeLimit limit number of trees
|
||||
* @param predLeaf prediction minimum to keep leafs
|
||||
* @return predict results
|
||||
*/
|
||||
private synchronized float[][] pred(DMatrix data, boolean outPutMargin, int treeLimit, boolean predLeaf) throws XGBoostError {
|
||||
int optionMask = 0;
|
||||
if(outPutMargin) {
|
||||
optionMask = 1;
|
||||
}
|
||||
if(predLeaf) {
|
||||
optionMask = 2;
|
||||
}
|
||||
float[][] rawPredicts = new float[1][];
|
||||
ErrorHandle.checkCall(XgboostJNI.XGBoosterPredict(handle, data.getHandle(), optionMask, treeLimit, rawPredicts));
|
||||
int row = (int) data.rowNum();
|
||||
int col = (int) rawPredicts[0].length/row;
|
||||
float[][] predicts = new float[row][col];
|
||||
int r,c;
|
||||
for(int i=0; i< rawPredicts[0].length; i++) {
|
||||
r = i/col;
|
||||
c = i%col;
|
||||
predicts[r][c] = rawPredicts[0][i];
|
||||
}
|
||||
return predicts;
|
||||
}
|
||||
|
||||
/**
|
||||
* Predict with data
|
||||
* @param data dmatrix storing the input
|
||||
* @return predict result
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public float[][] predict(DMatrix data) throws XGBoostError {
|
||||
return pred(data, false, 0, false);
|
||||
}
|
||||
|
||||
/**
|
||||
* Predict with data
|
||||
* @param data dmatrix storing the input
|
||||
* @param outPutMargin Whether to output the raw untransformed margin value.
|
||||
* @return predict result
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public float[][] predict(DMatrix data, boolean outPutMargin) throws XGBoostError {
|
||||
return pred(data, outPutMargin, 0, false);
|
||||
}
|
||||
|
||||
/**
|
||||
* Predict with data
|
||||
* @param data dmatrix storing the input
|
||||
* @param outPutMargin Whether to output the raw untransformed margin value.
|
||||
* @param treeLimit Limit number of trees in the prediction; defaults to 0 (use all trees).
|
||||
* @return predict result
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public float[][] predict(DMatrix data, boolean outPutMargin, int treeLimit) throws XGBoostError {
|
||||
return pred(data, outPutMargin, treeLimit, false);
|
||||
}
|
||||
|
||||
/**
|
||||
* Predict with data
|
||||
* @param data dmatrix storing the input
|
||||
* @param treeLimit Limit number of trees in the prediction; defaults to 0 (use all trees).
|
||||
* @param predLeaf When this option is on, the output will be a matrix of (nsample, ntrees), nsample = data.numRow
|
||||
with each record indicating the predicted leaf index of each sample in each tree.
|
||||
Note that the leaf index of a tree is unique per tree, so you may find leaf 1
|
||||
in both tree 1 and tree 0.
|
||||
* @return predict result
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public float[][] predict(DMatrix data , int treeLimit, boolean predLeaf) throws XGBoostError {
|
||||
return pred(data, false, treeLimit, predLeaf);
|
||||
}
|
||||
|
||||
/**
|
||||
* save model to modelPath
|
||||
* @param modelPath model path
|
||||
*/
|
||||
public void saveModel(String modelPath) {
|
||||
XgboostJNI.XGBoosterSaveModel(handle, modelPath);
|
||||
}
|
||||
|
||||
private void loadModel(String modelPath) {
|
||||
XgboostJNI.XGBoosterLoadModel(handle, modelPath);
|
||||
}
|
||||
|
||||
/**
|
||||
* get the dump of the model as a string array
|
||||
* @param withStats Controls whether the split statistics are output.
|
||||
* @return dumped model information
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public String[] getDumpInfo(boolean withStats) throws XGBoostError {
|
||||
int statsFlag = 0;
|
||||
if(withStats) {
|
||||
statsFlag = 1;
|
||||
}
|
||||
String[][] modelInfos = new String[1][];
|
||||
ErrorHandle.checkCall(XgboostJNI.XGBoosterDumpModel(handle, "", statsFlag, modelInfos));
|
||||
return modelInfos[0];
|
||||
}
|
||||
|
||||
/**
|
||||
* get the dump of the model as a string array
|
||||
* @param featureMap featureMap file
|
||||
* @param withStats Controls whether the split statistics are output.
|
||||
* @return dumped model information
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public String[] getDumpInfo(String featureMap, boolean withStats) throws XGBoostError {
|
||||
int statsFlag = 0;
|
||||
if(withStats) {
|
||||
statsFlag = 1;
|
||||
}
|
||||
String[][] modelInfos = new String[1][];
|
||||
ErrorHandle.checkCall(XgboostJNI.XGBoosterDumpModel(handle, featureMap, statsFlag, modelInfos));
|
||||
return modelInfos[0];
|
||||
}
|
||||
|
||||
/**
|
||||
* Dump model into a text file.
|
||||
* @param modelPath file to save dumped model info
|
||||
* @param withStats bool
|
||||
Controls whether the split statistics are output.
|
||||
* @throws FileNotFoundException file not found
|
||||
* @throws UnsupportedEncodingException unsupported feature
|
||||
* @throws IOException error with model writing
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public void dumpModel(String modelPath, boolean withStats) throws FileNotFoundException, UnsupportedEncodingException, IOException, XGBoostError {
|
||||
File tf = new File(modelPath);
|
||||
FileOutputStream out = new FileOutputStream(tf);
|
||||
BufferedWriter writer = new BufferedWriter(new OutputStreamWriter(out, "UTF-8"));
|
||||
String[] modelInfos = getDumpInfo(withStats);
|
||||
|
||||
for(int i=0; i<modelInfos.length; i++) {
|
||||
writer.write("booster [" + i +"]:\n");
|
||||
writer.write(modelInfos[i]);
|
||||
}
|
||||
|
||||
writer.close();
|
||||
out.close();
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* Dump model into a text file.
|
||||
* @param modelPath file to save dumped model info
|
||||
* @param featureMap featureMap file
|
||||
* @param withStats bool
|
||||
Controls whether the split statistics are output.
|
||||
* @throws FileNotFoundException exception
|
||||
* @throws UnsupportedEncodingException exception
|
||||
* @throws IOException exception
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public void dumpModel(String modelPath, String featureMap, boolean withStats) throws FileNotFoundException, UnsupportedEncodingException, IOException, XGBoostError {
|
||||
File tf = new File(modelPath);
|
||||
FileOutputStream out = new FileOutputStream(tf);
|
||||
BufferedWriter writer = new BufferedWriter(new OutputStreamWriter(out, "UTF-8"));
|
||||
String[] modelInfos = getDumpInfo(featureMap, withStats);
|
||||
|
||||
for(int i=0; i<modelInfos.length; i++) {
|
||||
writer.write("booster [" + i +"]:\n");
|
||||
writer.write(modelInfos[i]);
|
||||
}
|
||||
|
||||
writer.close();
|
||||
out.close();
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* get importance of each feature
|
||||
* @return featureMap key: feature index, value: feature importance score
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public Map<String, Integer> getFeatureScore() throws XGBoostError {
|
||||
String[] modelInfos = getDumpInfo(false);
|
||||
Map<String, Integer> featureScore = new HashMap<>();
|
||||
for(String tree : modelInfos) {
|
||||
for(String node : tree.split("\n")) {
|
||||
String[] array = node.split("\\[");
|
||||
if(array.length == 1) {
|
||||
continue;
|
||||
}
|
||||
String fid = array[1].split("\\]")[0];
|
||||
fid = fid.split("<")[0];
|
||||
if(featureScore.containsKey(fid)) {
|
||||
featureScore.put(fid, 1 + featureScore.get(fid));
|
||||
}
|
||||
else {
|
||||
featureScore.put(fid, 1);
|
||||
}
|
||||
}
|
||||
}
|
||||
return featureScore;
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* get importance of each feature
|
||||
* @param featureMap file to save dumped model info
|
||||
* @return featureMap key: feature index, value: feature importance score
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public Map<String, Integer> getFeatureScore(String featureMap) throws XGBoostError {
|
||||
String[] modelInfos = getDumpInfo(featureMap, false);
|
||||
Map<String, Integer> featureScore = new HashMap<>();
|
||||
for(String tree : modelInfos) {
|
||||
for(String node : tree.split("\n")) {
|
||||
String[] array = node.split("\\[");
|
||||
if(array.length == 1) {
|
||||
continue;
|
||||
}
|
||||
String fid = array[1].split("\\]")[0];
|
||||
fid = fid.split("<")[0];
|
||||
if(featureScore.containsKey(fid)) {
|
||||
featureScore.put(fid, 1 + featureScore.get(fid));
|
||||
}
|
||||
else {
|
||||
featureScore.put(fid, 1);
|
||||
}
|
||||
}
|
||||
}
|
||||
return featureScore;
|
||||
}
|
||||
|
||||
/**
|
||||
* transfer DMatrix array to handle array (used for native functions)
|
||||
* @param dmatrixs
|
||||
* @return handle array for input dmatrixs
|
||||
*/
|
||||
private static long[] dMatrixs2handles(DMatrix[] dmatrixs) {
|
||||
long[] handles = new long[dmatrixs.length];
|
||||
for(int i=0; i<dmatrixs.length; i++) {
|
||||
handles[i] = dmatrixs[i].getHandle();
|
||||
}
|
||||
return handles;
|
||||
}
|
||||
|
||||
@Override
|
||||
protected void finalize() {
|
||||
delete();
|
||||
}
|
||||
|
||||
public synchronized void delete() {
|
||||
if(handle != 0l) {
|
||||
XgboostJNI.XGBoosterFree(handle);
|
||||
handle=0;
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -1,268 +0,0 @@
|
||||
/*
|
||||
Copyright (c) 2014 by Contributors
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
*/
|
||||
package org.dmlc.xgboost4j;
|
||||
|
||||
import java.io.IOException;
|
||||
import org.apache.commons.logging.Log;
|
||||
import org.apache.commons.logging.LogFactory;
|
||||
import org.dmlc.xgboost4j.util.ErrorHandle;
|
||||
import org.dmlc.xgboost4j.util.XGBoostError;
|
||||
import org.dmlc.xgboost4j.util.Initializer;
|
||||
import org.dmlc.xgboost4j.wrapper.XgboostJNI;
|
||||
|
||||
/**
|
||||
* DMatrix for xgboost, similar to the python wrapper xgboost.py
|
||||
* @author hzx
|
||||
*/
|
||||
public class DMatrix {
|
||||
private static final Log logger = LogFactory.getLog(DMatrix.class);
|
||||
long handle = 0;
|
||||
|
||||
//load native library
|
||||
static {
|
||||
try {
|
||||
Initializer.InitXgboost();
|
||||
} catch (IOException ex) {
|
||||
logger.error("load native library failed.");
|
||||
logger.error(ex);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* sparse matrix type (CSR or CSC)
|
||||
*/
|
||||
public static enum SparseType {
|
||||
CSR,
|
||||
CSC;
|
||||
}
|
||||
|
||||
/**
|
||||
* init DMatrix from file (svmlight format)
|
||||
* @param dataPath path of data file
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public DMatrix(String dataPath) throws XGBoostError {
|
||||
if(dataPath == null) {
|
||||
throw new NullPointerException("dataPath: null");
|
||||
}
|
||||
long[] out = new long[1];
|
||||
ErrorHandle.checkCall(XgboostJNI.XGDMatrixCreateFromFile(dataPath, 1, out));
|
||||
handle = out[0];
|
||||
}
|
||||
|
||||
/**
|
||||
* create DMatrix from sparse matrix
|
||||
* @param headers index to headers (rowHeaders for CSR or colHeaders for CSC)
|
||||
* @param indices Indices (colIndexs for CSR or rowIndexs for CSC)
|
||||
* @param data non zero values (sequence by row for CSR or by col for CSC)
|
||||
* @param st sparse matrix type (CSR or CSC)
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public DMatrix(long[] headers, int[] indices, float[] data, SparseType st) throws XGBoostError {
|
||||
long[] out = new long[1];
|
||||
if(st == SparseType.CSR) {
|
||||
ErrorHandle.checkCall(XgboostJNI.XGDMatrixCreateFromCSR(headers, indices, data, out));
|
||||
}
|
||||
else if(st == SparseType.CSC) {
|
||||
ErrorHandle.checkCall(XgboostJNI.XGDMatrixCreateFromCSC(headers, indices, data, out));
|
||||
}
|
||||
else {
|
||||
throw new UnknownError("unknow sparsetype");
|
||||
}
|
||||
handle = out[0];
|
||||
}
|
||||
|
||||
/**
|
||||
* create DMatrix from dense matrix
|
||||
* @param data data values
|
||||
* @param nrow number of rows
|
||||
* @param ncol number of columns
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public DMatrix(float[] data, int nrow, int ncol) throws XGBoostError {
|
||||
long[] out = new long[1];
|
||||
ErrorHandle.checkCall(XgboostJNI.XGDMatrixCreateFromMat(data, nrow, ncol, 0.0f, out));
|
||||
handle = out[0];
|
||||
}
|
||||
|
||||
/**
|
||||
* used for DMatrix slice
|
||||
* @param handle
|
||||
*/
|
||||
private DMatrix(long handle) {
|
||||
this.handle = handle;
|
||||
}
|
||||
|
||||
|
||||
|
||||
/**
|
||||
* set label of dmatrix
|
||||
* @param labels labels
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public void setLabel(float[] labels) throws XGBoostError {
|
||||
ErrorHandle.checkCall(XgboostJNI.XGDMatrixSetFloatInfo(handle, "label", labels));
|
||||
}
|
||||
|
||||
/**
|
||||
* set weight of each instance
|
||||
* @param weights weights
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public void setWeight(float[] weights) throws XGBoostError {
|
||||
ErrorHandle.checkCall(XgboostJNI.XGDMatrixSetFloatInfo(handle, "weight", weights));
|
||||
}
|
||||
|
||||
/**
|
||||
* if specified, xgboost will start from this init margin
|
||||
* can be used to specify initial prediction to boost from
|
||||
* @param baseMargin base margin
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public void setBaseMargin(float[] baseMargin) throws XGBoostError {
|
||||
ErrorHandle.checkCall(XgboostJNI.XGDMatrixSetFloatInfo(handle, "base_margin", baseMargin));
|
||||
}
|
||||
|
||||
/**
|
||||
* if specified, xgboost will start from this init margin
|
||||
* can be used to specify initial prediction to boost from
|
||||
* @param baseMargin base margin
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public void setBaseMargin(float[][] baseMargin) throws XGBoostError {
|
||||
float[] flattenMargin = flatten(baseMargin);
|
||||
setBaseMargin(flattenMargin);
|
||||
}
|
||||
|
||||
/**
|
||||
* Set group sizes of DMatrix (used for ranking)
|
||||
* @param group group size as array
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public void setGroup(int[] group) throws XGBoostError {
|
||||
ErrorHandle.checkCall(XgboostJNI.XGDMatrixSetGroup(handle, group));
|
||||
}
|
||||
|
||||
private float[] getFloatInfo(String field) throws XGBoostError {
|
||||
float[][] infos = new float[1][];
|
||||
ErrorHandle.checkCall(XgboostJNI.XGDMatrixGetFloatInfo(handle, field, infos));
|
||||
return infos[0];
|
||||
}
|
||||
|
||||
private int[] getIntInfo(String field) throws XGBoostError {
|
||||
int[][] infos = new int[1][];
|
||||
ErrorHandle.checkCall(XgboostJNI.XGDMatrixGetUIntInfo(handle, field, infos));
|
||||
return infos[0];
|
||||
}
|
||||
|
||||
/**
|
||||
* get label values
|
||||
* @return label
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public float[] getLabel() throws XGBoostError {
|
||||
return getFloatInfo("label");
|
||||
}
|
||||
|
||||
/**
|
||||
* get weight of the DMatrix
|
||||
* @return weights
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public float[] getWeight() throws XGBoostError {
|
||||
return getFloatInfo("weight");
|
||||
}
|
||||
|
||||
/**
|
||||
* get base margin of the DMatrix
|
||||
* @return base margin
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public float[] getBaseMargin() throws XGBoostError {
|
||||
return getFloatInfo("base_margin");
|
||||
}
|
||||
|
||||
/**
|
||||
* Slice the DMatrix and return a new DMatrix that only contains `rowIndex`.
|
||||
* @param rowIndex row index
|
||||
* @return sliced new DMatrix
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public DMatrix slice(int[] rowIndex) throws XGBoostError {
|
||||
long[] out = new long[1];
|
||||
ErrorHandle.checkCall(XgboostJNI.XGDMatrixSliceDMatrix(handle, rowIndex, out));
|
||||
long sHandle = out[0];
|
||||
DMatrix sMatrix = new DMatrix(sHandle);
|
||||
return sMatrix;
|
||||
}
|
||||
|
||||
/**
|
||||
* get the row number of DMatrix
|
||||
* @return number of rows
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public long rowNum() throws XGBoostError {
|
||||
long[] rowNum = new long[1];
|
||||
ErrorHandle.checkCall(XgboostJNI.XGDMatrixNumRow(handle,rowNum));
|
||||
return rowNum[0];
|
||||
}
|
||||
|
||||
/**
|
||||
* save DMatrix to filePath
|
||||
* @param filePath file path
|
||||
*/
|
||||
public void saveBinary(String filePath) {
|
||||
XgboostJNI.XGDMatrixSaveBinary(handle, filePath, 1);
|
||||
}
|
||||
|
||||
/**
|
||||
* Get the handle
|
||||
* @return native handler id
|
||||
*/
|
||||
public long getHandle() {
|
||||
return handle;
|
||||
}
|
||||
|
||||
/**
|
||||
* flatten a mat to array
|
||||
* @param mat
|
||||
* @return
|
||||
*/
|
||||
private static float[] flatten(float[][] mat) {
|
||||
int size = 0;
|
||||
for (float[] array : mat) size += array.length;
|
||||
float[] result = new float[size];
|
||||
int pos = 0;
|
||||
for (float[] ar : mat) {
|
||||
System.arraycopy(ar, 0, result, pos, ar.length);
|
||||
pos += ar.length;
|
||||
}
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
@Override
|
||||
protected void finalize() {
|
||||
delete();
|
||||
}
|
||||
|
||||
public synchronized void delete() {
|
||||
if(handle != 0) {
|
||||
XgboostJNI.XGDMatrixFree(handle);
|
||||
handle = 0;
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -1,89 +0,0 @@
|
||||
/*
|
||||
Copyright (c) 2014 by Contributors
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
*/
|
||||
package org.dmlc.xgboost4j.util;
|
||||
|
||||
import java.util.Map;
|
||||
import org.dmlc.xgboost4j.IEvaluation;
|
||||
import org.dmlc.xgboost4j.Booster;
|
||||
import org.dmlc.xgboost4j.DMatrix;
|
||||
import org.dmlc.xgboost4j.IObjective;
|
||||
|
||||
/**
|
||||
* cross validation package for xgb
|
||||
* @author hzx
|
||||
*/
|
||||
public class CVPack {
|
||||
DMatrix dtrain;
|
||||
DMatrix dtest;
|
||||
DMatrix[] dmats;
|
||||
String[] names;
|
||||
Booster booster;
|
||||
|
||||
/**
|
||||
* create an cross validation package
|
||||
* @param dtrain train data
|
||||
* @param dtest test data
|
||||
* @param params parameters
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public CVPack(DMatrix dtrain, DMatrix dtest, Iterable<Map.Entry<String, Object>> params) throws XGBoostError {
|
||||
dmats = new DMatrix[] {dtrain, dtest};
|
||||
booster = new Booster(params, dmats);
|
||||
names = new String[] {"train", "test"};
|
||||
this.dtrain = dtrain;
|
||||
this.dtest = dtest;
|
||||
}
|
||||
|
||||
/**
|
||||
* update one iteration
|
||||
* @param iter iteration num
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public void update(int iter) throws XGBoostError {
|
||||
booster.update(dtrain, iter);
|
||||
}
|
||||
|
||||
/**
|
||||
* update one iteration
|
||||
* @param iter iteration num
|
||||
* @param obj customized objective
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public void update(int iter, IObjective obj) throws XGBoostError {
|
||||
booster.update(dtrain, iter, obj);
|
||||
}
|
||||
|
||||
/**
|
||||
* evaluation
|
||||
* @param iter iteration num
|
||||
* @return evaluation
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public String eval(int iter) throws XGBoostError {
|
||||
return booster.evalSet(dmats, names, iter);
|
||||
}
|
||||
|
||||
/**
|
||||
* evaluation
|
||||
* @param iter iteration num
|
||||
* @param eval customized eval
|
||||
* @return evaluation
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public String eval(int iter, IEvaluation eval) throws XGBoostError {
|
||||
return booster.evalSet(dmats, names, iter, eval);
|
||||
}
|
||||
}
|
||||
@ -1,49 +0,0 @@
|
||||
/*
|
||||
Copyright (c) 2014 by Contributors
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
*/
|
||||
package org.dmlc.xgboost4j.util;
|
||||
|
||||
import java.io.IOException;
|
||||
import org.apache.commons.logging.Log;
|
||||
import org.apache.commons.logging.LogFactory;
|
||||
import org.dmlc.xgboost4j.wrapper.XgboostJNI;
|
||||
|
||||
/**
|
||||
* Error handle for Xgboost.
|
||||
*/
|
||||
public class ErrorHandle {
|
||||
private static final Log logger = LogFactory.getLog(ErrorHandle.class);
|
||||
|
||||
//load native library
|
||||
static {
|
||||
try {
|
||||
Initializer.InitXgboost();
|
||||
} catch (IOException ex) {
|
||||
logger.error("load native library failed.");
|
||||
logger.error(ex);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Check the return value of C API.
|
||||
* @param ret return valud of xgboostJNI C API call
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public static void checkCall(int ret) throws XGBoostError {
|
||||
if(ret != 0) {
|
||||
throw new XGBoostError(XgboostJNI.XGBGetLastError());
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -1,92 +0,0 @@
|
||||
/*
|
||||
Copyright (c) 2014 by Contributors
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
*/
|
||||
package org.dmlc.xgboost4j.util;
|
||||
|
||||
import java.io.IOException;
|
||||
import java.lang.reflect.Field;
|
||||
|
||||
import org.apache.commons.logging.Log;
|
||||
import org.apache.commons.logging.LogFactory;
|
||||
|
||||
/**
|
||||
* class to load native library
|
||||
* @author hzx
|
||||
*/
|
||||
public class Initializer {
|
||||
private static final Log logger = LogFactory.getLog(Initializer.class);
|
||||
|
||||
static boolean initialized = false;
|
||||
public static final String nativePath = "./lib";
|
||||
public static final String nativeResourcePath = "/lib/";
|
||||
public static final String[] libNames = new String[] {"xgboost4j"};
|
||||
|
||||
public static synchronized void InitXgboost() throws IOException {
|
||||
if(initialized == false) {
|
||||
for(String libName: libNames) {
|
||||
smartLoad(libName);
|
||||
}
|
||||
initialized = true;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* load native library, this method will first try to load library from java.library.path, then try to load library in jar package.
|
||||
* @param libName library path
|
||||
* @throws IOException exception
|
||||
*/
|
||||
private static void smartLoad(String libName) throws IOException {
|
||||
addNativeDir(nativePath);
|
||||
try {
|
||||
System.loadLibrary(libName);
|
||||
}
|
||||
catch (UnsatisfiedLinkError e) {
|
||||
try {
|
||||
NativeUtils.loadLibraryFromJar(nativeResourcePath + System.mapLibraryName(libName));
|
||||
}
|
||||
catch (IOException e1) {
|
||||
throw e1;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Add libPath to java.library.path, then native library in libPath would be load properly
|
||||
* @param libPath library path
|
||||
* @throws IOException exception
|
||||
*/
|
||||
public static void addNativeDir(String libPath) throws IOException {
|
||||
try {
|
||||
Field field = ClassLoader.class.getDeclaredField("usr_paths");
|
||||
field.setAccessible(true);
|
||||
String[] paths = (String[]) field.get(null);
|
||||
for (String path : paths) {
|
||||
if (libPath.equals(path)) {
|
||||
return;
|
||||
}
|
||||
}
|
||||
String[] tmp = new String[paths.length+1];
|
||||
System.arraycopy(paths,0,tmp,0,paths.length);
|
||||
tmp[paths.length] = libPath;
|
||||
field.set(null, tmp);
|
||||
} catch (IllegalAccessException e) {
|
||||
logger.error(e.getMessage());
|
||||
throw new IOException("Failed to get permissions to set library path");
|
||||
} catch (NoSuchFieldException e) {
|
||||
logger.error(e.getMessage());
|
||||
throw new IOException("Failed to get field handle to set library path");
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -1,113 +0,0 @@
|
||||
/*
|
||||
Copyright (c) 2014 by Contributors
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
*/
|
||||
package org.dmlc.xgboost4j.util;
|
||||
|
||||
import java.io.File;
|
||||
import java.io.FileNotFoundException;
|
||||
import java.io.FileOutputStream;
|
||||
import java.io.IOException;
|
||||
import java.io.InputStream;
|
||||
import java.io.OutputStream;
|
||||
|
||||
|
||||
/**
|
||||
* Simple library class for working with JNI (Java Native Interface)
|
||||
* <p>
|
||||
* See <a href="http://adamheinrich.com/2012/how-to-load-native-jni-library-from-jar">
|
||||
* http://adamheinrich.com/2012/how-to-load-native-jni-library-from-jar</a>
|
||||
* <p>
|
||||
* Author Adam Heirnich <adam@adamh.cz>, http://www.adamh.cz
|
||||
*/
|
||||
public class NativeUtils {
|
||||
|
||||
/**
|
||||
* Private constructor - this class will never be instanced
|
||||
*/
|
||||
private NativeUtils() {
|
||||
}
|
||||
|
||||
/**
|
||||
* Loads library from current JAR archive
|
||||
* <p>
|
||||
* The file from JAR is copied into system temporary directory and then loaded.
|
||||
* The temporary file is deleted after exiting.
|
||||
* Method uses String as filename because the pathname is "abstract", not system-dependent.
|
||||
* <p>
|
||||
* The restrictions of {@link File#createTempFile(java.lang.String, java.lang.String)} apply to {@code path}.
|
||||
*
|
||||
* @param path The filename inside JAR as absolute path (beginning with '/'), e.g. /package/File.ext
|
||||
* @throws IOException If temporary file creation or read/write operation fails
|
||||
* @throws IllegalArgumentException If source file (param path) does not exist
|
||||
* @throws IllegalArgumentException If the path is not absolute or if the filename is shorter than three characters
|
||||
*/
|
||||
public static void loadLibraryFromJar(String path) throws IOException {
|
||||
|
||||
if (!path.startsWith("/")) {
|
||||
throw new IllegalArgumentException("The path has to be absolute (start with '/').");
|
||||
}
|
||||
|
||||
// Obtain filename from path
|
||||
String[] parts = path.split("/");
|
||||
String filename = (parts.length > 1) ? parts[parts.length - 1] : null;
|
||||
|
||||
// Split filename to prexif and suffix (extension)
|
||||
String prefix = "";
|
||||
String suffix = null;
|
||||
if (filename != null) {
|
||||
parts = filename.split("\\.", 2);
|
||||
prefix = parts[0];
|
||||
suffix = (parts.length > 1) ? "."+parts[parts.length - 1] : null; // Thanks, davs! :-)
|
||||
}
|
||||
|
||||
// Check if the filename is okay
|
||||
if (filename == null || prefix.length() < 3) {
|
||||
throw new IllegalArgumentException("The filename has to be at least 3 characters long.");
|
||||
}
|
||||
|
||||
// Prepare temporary file
|
||||
File temp = File.createTempFile(prefix, suffix);
|
||||
temp.deleteOnExit();
|
||||
|
||||
if (!temp.exists()) {
|
||||
throw new FileNotFoundException("File " + temp.getAbsolutePath() + " does not exist.");
|
||||
}
|
||||
|
||||
// Prepare buffer for data copying
|
||||
byte[] buffer = new byte[1024];
|
||||
int readBytes;
|
||||
|
||||
// Open and check input stream
|
||||
InputStream is = NativeUtils.class.getResourceAsStream(path);
|
||||
if (is == null) {
|
||||
throw new FileNotFoundException("File " + path + " was not found inside JAR.");
|
||||
}
|
||||
|
||||
// Open output stream and copy data between source file in JAR and the temporary file
|
||||
OutputStream os = new FileOutputStream(temp);
|
||||
try {
|
||||
while ((readBytes = is.read(buffer)) != -1) {
|
||||
os.write(buffer, 0, readBytes);
|
||||
}
|
||||
} finally {
|
||||
// If read/write fails, close streams safely before throwing an exception
|
||||
os.close();
|
||||
is.close();
|
||||
}
|
||||
|
||||
// Finally, load the library
|
||||
System.load(temp.getAbsolutePath());
|
||||
}
|
||||
}
|
||||
@ -1,238 +0,0 @@
|
||||
/*
|
||||
Copyright (c) 2014 by Contributors
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
*/
|
||||
package org.dmlc.xgboost4j.util;
|
||||
|
||||
import java.util.ArrayList;
|
||||
import java.util.Collections;
|
||||
import java.util.HashMap;
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
import java.util.Map.Entry;
|
||||
import org.apache.commons.logging.Log;
|
||||
import org.apache.commons.logging.LogFactory;
|
||||
import org.dmlc.xgboost4j.IEvaluation;
|
||||
import org.dmlc.xgboost4j.Booster;
|
||||
import org.dmlc.xgboost4j.DMatrix;
|
||||
import org.dmlc.xgboost4j.IObjective;
|
||||
|
||||
|
||||
/**
|
||||
* trainer for xgboost
|
||||
* @author hzx
|
||||
*/
|
||||
public class Trainer {
|
||||
private static final Log logger = LogFactory.getLog(Trainer.class);
|
||||
|
||||
/**
|
||||
* Train a booster with given parameters.
|
||||
* @param params Booster params.
|
||||
* @param dtrain Data to be trained.
|
||||
* @param round Number of boosting iterations.
|
||||
* @param watchs a group of items to be evaluated during training, this allows user to watch performance on the validation set.
|
||||
* @param obj customized objective (set to null if not used)
|
||||
* @param eval customized evaluation (set to null if not used)
|
||||
* @return trained booster
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public static Booster train(Iterable<Entry<String, Object>> params, DMatrix dtrain, int round,
|
||||
Iterable<Entry<String, DMatrix>> watchs, IObjective obj, IEvaluation eval) throws XGBoostError {
|
||||
|
||||
//collect eval matrixs
|
||||
String[] evalNames;
|
||||
DMatrix[] evalMats;
|
||||
List<String> names = new ArrayList<>();
|
||||
List<DMatrix> mats = new ArrayList<>();
|
||||
|
||||
for(Entry<String, DMatrix> evalEntry : watchs) {
|
||||
names.add(evalEntry.getKey());
|
||||
mats.add(evalEntry.getValue());
|
||||
}
|
||||
|
||||
evalNames = names.toArray(new String[names.size()]);
|
||||
evalMats = mats.toArray(new DMatrix[mats.size()]);
|
||||
|
||||
//collect all data matrixs
|
||||
DMatrix[] allMats;
|
||||
if(evalMats!=null && evalMats.length>0) {
|
||||
allMats = new DMatrix[evalMats.length+1];
|
||||
allMats[0] = dtrain;
|
||||
System.arraycopy(evalMats, 0, allMats, 1, evalMats.length);
|
||||
}
|
||||
else {
|
||||
allMats = new DMatrix[1];
|
||||
allMats[0] = dtrain;
|
||||
}
|
||||
|
||||
//initialize booster
|
||||
Booster booster = new Booster(params, allMats);
|
||||
|
||||
//begin to train
|
||||
for(int iter=0; iter<round; iter++) {
|
||||
if(obj != null) {
|
||||
booster.update(dtrain, iter, obj);
|
||||
} else {
|
||||
booster.update(dtrain, iter);
|
||||
}
|
||||
|
||||
//evaluation
|
||||
if(evalMats!=null && evalMats.length>0) {
|
||||
String evalInfo;
|
||||
if(eval != null) {
|
||||
evalInfo = booster.evalSet(evalMats, evalNames, iter, eval);
|
||||
}
|
||||
else {
|
||||
evalInfo = booster.evalSet(evalMats, evalNames, iter);
|
||||
}
|
||||
logger.info(evalInfo);
|
||||
}
|
||||
}
|
||||
return booster;
|
||||
}
|
||||
|
||||
/**
|
||||
* Cross-validation with given paramaters.
|
||||
* @param params Booster params.
|
||||
* @param data Data to be trained.
|
||||
* @param round Number of boosting iterations.
|
||||
* @param nfold Number of folds in CV.
|
||||
* @param metrics Evaluation metrics to be watched in CV.
|
||||
* @param obj customized objective (set to null if not used)
|
||||
* @param eval customized evaluation (set to null if not used)
|
||||
* @return evaluation history
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public static String[] crossValiation(Iterable<Entry<String, Object>> params, DMatrix data, int round, int nfold, String[] metrics, IObjective obj, IEvaluation eval) throws XGBoostError {
|
||||
CVPack[] cvPacks = makeNFold(data, nfold, params, metrics);
|
||||
String[] evalHist = new String[round];
|
||||
String[] results = new String[cvPacks.length];
|
||||
for(int i=0; i<round; i++) {
|
||||
for(CVPack cvPack : cvPacks) {
|
||||
if(obj != null) {
|
||||
cvPack.update(i, obj);
|
||||
}
|
||||
else {
|
||||
cvPack.update(i);
|
||||
}
|
||||
}
|
||||
|
||||
for(int j=0; j<cvPacks.length; j++) {
|
||||
if(eval != null) {
|
||||
results[j] = cvPacks[j].eval(i, eval);
|
||||
}
|
||||
else {
|
||||
results[j] = cvPacks[j].eval(i);
|
||||
}
|
||||
}
|
||||
|
||||
evalHist[i] = aggCVResults(results);
|
||||
logger.info(evalHist[i]);
|
||||
}
|
||||
return evalHist;
|
||||
}
|
||||
|
||||
/**
|
||||
* make an n-fold array of CVPack from random indices
|
||||
* @param data original data
|
||||
* @param nfold num of folds
|
||||
* @param params booster parameters
|
||||
* @param evalMetrics Evaluation metrics
|
||||
* @return CV package array
|
||||
* @throws org.dmlc.xgboost4j.util.XGBoostError native error
|
||||
*/
|
||||
public static CVPack[] makeNFold(DMatrix data, int nfold, Iterable<Entry<String, Object>> params, String[] evalMetrics) throws XGBoostError {
|
||||
List<Integer> samples = genRandPermutationNums(0, (int) data.rowNum());
|
||||
int step = samples.size()/nfold;
|
||||
int[] testSlice = new int[step];
|
||||
int[] trainSlice = new int[samples.size()-step];
|
||||
int testid, trainid;
|
||||
CVPack[] cvPacks = new CVPack[nfold];
|
||||
for(int i=0; i<nfold; i++) {
|
||||
testid = 0;
|
||||
trainid = 0;
|
||||
for(int j=0; j<samples.size(); j++) {
|
||||
if(j>(i*step) && j<(i*step+step) && testid<step) {
|
||||
testSlice[testid] = samples.get(j);
|
||||
testid++;
|
||||
}
|
||||
else{
|
||||
if(trainid<samples.size()-step) {
|
||||
trainSlice[trainid] = samples.get(j);
|
||||
trainid++;
|
||||
}
|
||||
else {
|
||||
testSlice[testid] = samples.get(j);
|
||||
testid++;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
DMatrix dtrain = data.slice(trainSlice);
|
||||
DMatrix dtest = data.slice(testSlice);
|
||||
CVPack cvPack = new CVPack(dtrain, dtest, params);
|
||||
//set eval types
|
||||
if(evalMetrics!=null) {
|
||||
for(String type : evalMetrics) {
|
||||
cvPack.booster.setParam("eval_metric", type);
|
||||
}
|
||||
}
|
||||
cvPacks[i] = cvPack;
|
||||
}
|
||||
|
||||
return cvPacks;
|
||||
}
|
||||
|
||||
private static List<Integer> genRandPermutationNums(int start, int end) {
|
||||
List<Integer> samples = new ArrayList<>();
|
||||
for(int i=start; i<end; i++) {
|
||||
samples.add(i);
|
||||
}
|
||||
Collections.shuffle(samples);
|
||||
return samples;
|
||||
}
|
||||
|
||||
/**
|
||||
* Aggregate cross-validation results.
|
||||
* @param results eval info from each data sample
|
||||
* @return cross-validation eval info
|
||||
*/
|
||||
public static String aggCVResults(String[] results) {
|
||||
Map<String, List<Float> > cvMap = new HashMap<>();
|
||||
String aggResult = results[0].split("\t")[0];
|
||||
for(String result : results) {
|
||||
String[] items = result.split("\t");
|
||||
for(int i=1; i<items.length; i++) {
|
||||
String[] tup = items[i].split(":");
|
||||
String key = tup[0];
|
||||
Float value = Float.valueOf(tup[1]);
|
||||
if(!cvMap.containsKey(key)) {
|
||||
cvMap.put(key, new ArrayList<Float>());
|
||||
}
|
||||
cvMap.get(key).add(value);
|
||||
}
|
||||
}
|
||||
|
||||
for(String key : cvMap.keySet()) {
|
||||
float value = 0f;
|
||||
for(Float tvalue : cvMap.get(key)) {
|
||||
value += tvalue;
|
||||
}
|
||||
value /= cvMap.get(key).size();
|
||||
aggResult += String.format("\tcv-%s:%f", key, value);
|
||||
}
|
||||
|
||||
return aggResult;
|
||||
}
|
||||
}
|
||||
@ -1,142 +0,0 @@
|
||||
/*
|
||||
Copyright (c) 2014 by Contributors
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
*/
|
||||
package org.dmlc.xgboost4j;
|
||||
|
||||
import java.util.AbstractMap;
|
||||
import java.util.ArrayList;
|
||||
import java.util.HashMap;
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
import java.util.Map.Entry;
|
||||
import junit.framework.TestCase;
|
||||
import org.apache.commons.logging.Log;
|
||||
import org.apache.commons.logging.LogFactory;
|
||||
import org.dmlc.xgboost4j.util.Trainer;
|
||||
import org.dmlc.xgboost4j.util.XGBoostError;
|
||||
import org.junit.Test;
|
||||
|
||||
/**
|
||||
* test cases for Booster
|
||||
* @author hzx
|
||||
*/
|
||||
public class BoosterTest {
|
||||
public static class EvalError implements IEvaluation {
|
||||
private static final Log logger = LogFactory.getLog(EvalError.class);
|
||||
|
||||
String evalMetric = "custom_error";
|
||||
|
||||
public EvalError() {
|
||||
}
|
||||
|
||||
@Override
|
||||
public String getMetric() {
|
||||
return evalMetric;
|
||||
}
|
||||
|
||||
@Override
|
||||
public float eval(float[][] predicts, DMatrix dmat) {
|
||||
float error = 0f;
|
||||
float[] labels;
|
||||
try {
|
||||
labels = dmat.getLabel();
|
||||
} catch (XGBoostError ex) {
|
||||
logger.error(ex);
|
||||
return -1f;
|
||||
}
|
||||
int nrow = predicts.length;
|
||||
for(int i=0; i<nrow; i++) {
|
||||
if(labels[i]==0f && predicts[i][0]>0) {
|
||||
error++;
|
||||
}
|
||||
else if(labels[i]==1f && predicts[i][0]<=0) {
|
||||
error++;
|
||||
}
|
||||
}
|
||||
|
||||
return error/labels.length;
|
||||
}
|
||||
}
|
||||
|
||||
@Test
|
||||
public void testBoosterBasic() throws XGBoostError {
|
||||
DMatrix trainMat = new DMatrix("../../demo/data/agaricus.txt.train");
|
||||
DMatrix testMat = new DMatrix("../../demo/data/agaricus.txt.test");
|
||||
|
||||
//set params
|
||||
Map<String, Object> paramMap = new HashMap<String, Object>() {
|
||||
{
|
||||
put("eta", 1.0);
|
||||
put("max_depth", 2);
|
||||
put("silent", 1);
|
||||
put("objective", "binary:logistic");
|
||||
}
|
||||
};
|
||||
Iterable<Entry<String, Object>> param = paramMap.entrySet();
|
||||
|
||||
//set watchList
|
||||
List<Entry<String, DMatrix>> watchs = new ArrayList<>();
|
||||
watchs.add(new AbstractMap.SimpleEntry<>("train", trainMat));
|
||||
watchs.add(new AbstractMap.SimpleEntry<>("test", testMat));
|
||||
|
||||
//set round
|
||||
int round = 2;
|
||||
|
||||
//train a boost model
|
||||
Booster booster = Trainer.train(param, trainMat, round, watchs, null, null);
|
||||
|
||||
//predict raw output
|
||||
float[][] predicts = booster.predict(testMat, true);
|
||||
|
||||
//eval
|
||||
IEvaluation eval = new EvalError();
|
||||
//error must be less than 0.1
|
||||
TestCase.assertTrue(eval.eval(predicts, testMat)<0.1f);
|
||||
|
||||
//test dump model
|
||||
|
||||
}
|
||||
|
||||
/**
|
||||
* test cross valiation
|
||||
* @throws XGBoostError
|
||||
*/
|
||||
@Test
|
||||
public void testCV() throws XGBoostError {
|
||||
//load train mat
|
||||
DMatrix trainMat = new DMatrix("../../demo/data/agaricus.txt.train");
|
||||
|
||||
//set params
|
||||
Map<String, Object> param= new HashMap<String, Object>() {
|
||||
{
|
||||
put("eta", 1.0);
|
||||
put("max_depth", 3);
|
||||
put("silent", 1);
|
||||
put("nthread", 6);
|
||||
put("objective", "binary:logistic");
|
||||
put("gamma", 1.0);
|
||||
put("eval_metric", "error");
|
||||
}
|
||||
};
|
||||
|
||||
//do 5-fold cross validation
|
||||
int round = 2;
|
||||
int nfold = 5;
|
||||
//set additional eval_metrics
|
||||
String[] metrics = null;
|
||||
|
||||
String[] evalHist = Trainer.crossValiation(param.entrySet(), trainMat, round, nfold, metrics, null, null);
|
||||
}
|
||||
}
|
||||
@ -1,102 +0,0 @@
|
||||
/*
|
||||
Copyright (c) 2014 by Contributors
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
*/
|
||||
package org.dmlc.xgboost4j;
|
||||
|
||||
import java.util.Arrays;
|
||||
import java.util.Random;
|
||||
import junit.framework.TestCase;
|
||||
import org.dmlc.xgboost4j.util.XGBoostError;
|
||||
import org.junit.Test;
|
||||
|
||||
/**
|
||||
* test cases for DMatrix
|
||||
* @author hzx
|
||||
*/
|
||||
public class DMatrixTest {
|
||||
|
||||
@Test
|
||||
public void testCreateFromFile() throws XGBoostError {
|
||||
//create DMatrix from file
|
||||
DMatrix dmat = new DMatrix("../../demo/data/agaricus.txt.test");
|
||||
//get label
|
||||
float[] labels = dmat.getLabel();
|
||||
//check length
|
||||
TestCase.assertTrue(dmat.rowNum()==labels.length);
|
||||
//set weights
|
||||
float[] weights = Arrays.copyOf(labels, labels.length);
|
||||
dmat.setWeight(weights);
|
||||
float[] dweights = dmat.getWeight();
|
||||
TestCase.assertTrue(Arrays.equals(weights, dweights));
|
||||
}
|
||||
|
||||
@Test
|
||||
public void testCreateFromCSR() throws XGBoostError {
|
||||
//create Matrix from csr format sparse Matrix and labels
|
||||
/**
|
||||
* sparse matrix
|
||||
* 1 0 2 3 0
|
||||
* 4 0 2 3 5
|
||||
* 3 1 2 5 0
|
||||
*/
|
||||
float[] data = new float[] {1, 2, 3, 4, 2, 3, 5, 3, 1, 2, 5};
|
||||
int[] colIndex = new int[] {0, 2, 3, 0, 2, 3, 4, 0, 1, 2, 3};
|
||||
long[] rowHeaders = new long[] {0, 3, 7, 11};
|
||||
DMatrix dmat1 = new DMatrix(rowHeaders, colIndex, data, DMatrix.SparseType.CSR);
|
||||
//check row num
|
||||
System.out.println(dmat1.rowNum());
|
||||
TestCase.assertTrue(dmat1.rowNum()==3);
|
||||
//test set label
|
||||
float[] label1 = new float[] {1, 0, 1};
|
||||
dmat1.setLabel(label1);
|
||||
float[] label2 = dmat1.getLabel();
|
||||
TestCase.assertTrue(Arrays.equals(label1, label2));
|
||||
}
|
||||
|
||||
@Test
|
||||
public void testCreateFromDenseMatrix() throws XGBoostError {
|
||||
//create DMatrix from 10*5 dense matrix
|
||||
int nrow = 10;
|
||||
int ncol = 5;
|
||||
float[] data0 = new float[nrow*ncol];
|
||||
//put random nums
|
||||
Random random = new Random();
|
||||
for(int i=0; i<nrow*ncol; i++) {
|
||||
data0[i] = random.nextFloat();
|
||||
}
|
||||
|
||||
//create label
|
||||
float[] label0 = new float[nrow];
|
||||
for(int i=0; i<nrow; i++) {
|
||||
label0[i] = random.nextFloat();
|
||||
}
|
||||
|
||||
DMatrix dmat0 = new DMatrix(data0, nrow, ncol);
|
||||
dmat0.setLabel(label0);
|
||||
|
||||
//check
|
||||
TestCase.assertTrue(dmat0.rowNum()==10);
|
||||
TestCase.assertTrue(dmat0.getLabel().length==10);
|
||||
|
||||
//set weights for each instance
|
||||
float[] weights = new float[nrow];
|
||||
for(int i=0; i<nrow; i++) {
|
||||
weights[i] = random.nextFloat();
|
||||
}
|
||||
dmat0.setWeight(weights);
|
||||
|
||||
TestCase.assertTrue(Arrays.equals(weights, dmat0.getWeight()));
|
||||
}
|
||||
}
|
||||
@ -1,221 +0,0 @@
|
||||
/* DO NOT EDIT THIS FILE - it is machine generated */
|
||||
#include <jni.h>
|
||||
/* Header for class org_dmlc_xgboost4j_wrapper_XgboostJNI */
|
||||
|
||||
#ifndef _Included_org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
#define _Included_org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
#ifdef __cplusplus
|
||||
extern "C" {
|
||||
#endif
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Method: XGBGetLastError
|
||||
* Signature: ()Ljava/lang/String;
|
||||
*/
|
||||
JNIEXPORT jstring JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBGetLastError
|
||||
(JNIEnv *, jclass);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Method: XGDMatrixCreateFromFile
|
||||
* Signature: (Ljava/lang/String;I[J)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixCreateFromFile
|
||||
(JNIEnv *, jclass, jstring, jint, jlongArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Method: XGDMatrixCreateFromCSR
|
||||
* Signature: ([J[I[F[J)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixCreateFromCSR
|
||||
(JNIEnv *, jclass, jlongArray, jintArray, jfloatArray, jlongArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Method: XGDMatrixCreateFromCSC
|
||||
* Signature: ([J[I[F[J)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixCreateFromCSC
|
||||
(JNIEnv *, jclass, jlongArray, jintArray, jfloatArray, jlongArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Method: XGDMatrixCreateFromMat
|
||||
* Signature: ([FIIF[J)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixCreateFromMat
|
||||
(JNIEnv *, jclass, jfloatArray, jint, jint, jfloat, jlongArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Method: XGDMatrixSliceDMatrix
|
||||
* Signature: (J[I[J)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixSliceDMatrix
|
||||
(JNIEnv *, jclass, jlong, jintArray, jlongArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Method: XGDMatrixFree
|
||||
* Signature: (J)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixFree
|
||||
(JNIEnv *, jclass, jlong);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Method: XGDMatrixSaveBinary
|
||||
* Signature: (JLjava/lang/String;I)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixSaveBinary
|
||||
(JNIEnv *, jclass, jlong, jstring, jint);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Method: XGDMatrixSetFloatInfo
|
||||
* Signature: (JLjava/lang/String;[F)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixSetFloatInfo
|
||||
(JNIEnv *, jclass, jlong, jstring, jfloatArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Method: XGDMatrixSetUIntInfo
|
||||
* Signature: (JLjava/lang/String;[I)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixSetUIntInfo
|
||||
(JNIEnv *, jclass, jlong, jstring, jintArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Method: XGDMatrixSetGroup
|
||||
* Signature: (J[I)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixSetGroup
|
||||
(JNIEnv *, jclass, jlong, jintArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Method: XGDMatrixGetFloatInfo
|
||||
* Signature: (JLjava/lang/String;[[F)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixGetFloatInfo
|
||||
(JNIEnv *, jclass, jlong, jstring, jobjectArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Method: XGDMatrixGetUIntInfo
|
||||
* Signature: (JLjava/lang/String;[[I)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixGetUIntInfo
|
||||
(JNIEnv *, jclass, jlong, jstring, jobjectArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Method: XGDMatrixNumRow
|
||||
* Signature: (J[J)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixNumRow
|
||||
(JNIEnv *, jclass, jlong, jlongArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Method: XGBoosterCreate
|
||||
* Signature: ([J[J)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterCreate
|
||||
(JNIEnv *, jclass, jlongArray, jlongArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Method: XGBoosterFree
|
||||
* Signature: (J)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterFree
|
||||
(JNIEnv *, jclass, jlong);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Method: XGBoosterSetParam
|
||||
* Signature: (JLjava/lang/String;Ljava/lang/String;)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterSetParam
|
||||
(JNIEnv *, jclass, jlong, jstring, jstring);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Method: XGBoosterUpdateOneIter
|
||||
* Signature: (JIJ)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterUpdateOneIter
|
||||
(JNIEnv *, jclass, jlong, jint, jlong);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Method: XGBoosterBoostOneIter
|
||||
* Signature: (JJ[F[F)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterBoostOneIter
|
||||
(JNIEnv *, jclass, jlong, jlong, jfloatArray, jfloatArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Method: XGBoosterEvalOneIter
|
||||
* Signature: (JI[J[Ljava/lang/String;[Ljava/lang/String;)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterEvalOneIter
|
||||
(JNIEnv *, jclass, jlong, jint, jlongArray, jobjectArray, jobjectArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Method: XGBoosterPredict
|
||||
* Signature: (JJIJ[[F)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterPredict
|
||||
(JNIEnv *, jclass, jlong, jlong, jint, jint, jobjectArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Method: XGBoosterLoadModel
|
||||
* Signature: (JLjava/lang/String;)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterLoadModel
|
||||
(JNIEnv *, jclass, jlong, jstring);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Method: XGBoosterSaveModel
|
||||
* Signature: (JLjava/lang/String;)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterSaveModel
|
||||
(JNIEnv *, jclass, jlong, jstring);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Method: XGBoosterLoadModelFromBuffer
|
||||
* Signature: (JJJ)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterLoadModelFromBuffer
|
||||
(JNIEnv *, jclass, jlong, jlong, jlong);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Method: XGBoosterGetModelRaw
|
||||
* Signature: (J[Ljava/lang/String;)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterGetModelRaw
|
||||
(JNIEnv *, jclass, jlong, jobjectArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Method: XGBoosterDumpModel
|
||||
* Signature: (JLjava/lang/String;I[[Ljava/lang/String;)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterDumpModel
|
||||
(JNIEnv *, jclass, jlong, jstring, jint, jobjectArray);
|
||||
|
||||
#ifdef __cplusplus
|
||||
}
|
||||
#endif
|
||||
#endif
|
||||
@ -16,8 +16,8 @@ if [ $(uname) == "Darwin" ]; then
|
||||
fi
|
||||
|
||||
cd ..
|
||||
make java no_omp=${dis_omp}
|
||||
cd java
|
||||
make jvm-packages no_omp=${dis_omp}
|
||||
cd jvm-packages
|
||||
echo "move native lib"
|
||||
|
||||
libPath="xgboost4j/src/main/resources/lib"
|
||||
@ -26,7 +26,7 @@ if [ ! -d "$libPath" ]; then
|
||||
fi
|
||||
|
||||
rm -f xgboost4j/src/main/resources/lib/libxgboost4j.${dl}
|
||||
mv libxgboost4j.so xgboost4j/src/main/resources/lib/libxgboost4j.${dl}
|
||||
mv lib/libxgboost4j.so xgboost4j/src/main/resources/lib/libxgboost4j.${dl}
|
||||
|
||||
popd > /dev/null
|
||||
echo "complete"
|
||||
85
jvm-packages/pom.xml
Normal file
85
jvm-packages/pom.xml
Normal file
@ -0,0 +1,85 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<project xmlns="http://maven.apache.org/POM/4.0.0"
|
||||
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
|
||||
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
|
||||
<modelVersion>4.0.0</modelVersion>
|
||||
|
||||
<groupId>org.dmlc</groupId>
|
||||
<artifactId>xgboostjvm</artifactId>
|
||||
<version>0.1</version>
|
||||
<packaging>pom</packaging>
|
||||
<properties>
|
||||
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
|
||||
<project.reporting.outputEncoding>UTF-8</project.reporting.outputEncoding>
|
||||
<maven.compiler.source>1.7</maven.compiler.source>
|
||||
<maven.compiler.target>1.7</maven.compiler.target>
|
||||
<maven.version>3.3.9</maven.version>
|
||||
<scala.version>2.11.7</scala.version>
|
||||
<scala.binary.version>2.11</scala.binary.version>
|
||||
</properties>
|
||||
<modules>
|
||||
<module>xgboost4j</module>
|
||||
<module>xgboost4j-demo</module>
|
||||
</modules>
|
||||
<build>
|
||||
<plugins>
|
||||
<plugin>
|
||||
<groupId>net.alchim31.maven</groupId>
|
||||
<artifactId>scala-maven-plugin</artifactId>
|
||||
<version>3.2.2</version>
|
||||
<executions>
|
||||
<execution>
|
||||
<id>compile</id>
|
||||
<goals>
|
||||
<goal>compile</goal>
|
||||
</goals>
|
||||
<phase>compile</phase>
|
||||
</execution>
|
||||
<execution>
|
||||
<id>test-compile</id>
|
||||
<goals>
|
||||
<goal>testCompile</goal>
|
||||
</goals>
|
||||
<phase>test-compile</phase>
|
||||
</execution>
|
||||
<execution>
|
||||
<phase>process-resources</phase>
|
||||
<goals>
|
||||
<goal>compile</goal>
|
||||
</goals>
|
||||
</execution>
|
||||
</executions>
|
||||
</plugin>
|
||||
<plugin>
|
||||
<groupId>org.apache.maven.plugins</groupId>
|
||||
<artifactId>maven-surefire-plugin</artifactId>
|
||||
<configuration>
|
||||
<argLine>-Djava.library.path=lib/</argLine>
|
||||
</configuration>
|
||||
</plugin>
|
||||
</plugins>
|
||||
</build>
|
||||
<dependencies>
|
||||
<dependency>
|
||||
<groupId>commons-logging</groupId>
|
||||
<artifactId>commons-logging</artifactId>
|
||||
<version>1.2</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.scala-lang</groupId>
|
||||
<artifactId>scala-compiler</artifactId>
|
||||
<version>${scala.version}</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.scala-lang</groupId>
|
||||
<artifactId>scala-library</artifactId>
|
||||
<version>${scala.version}</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.scalatest</groupId>
|
||||
<artifactId>scalatest_${scala.binary.version}</artifactId>
|
||||
<version>2.2.6</version>
|
||||
<scope>test</scope>
|
||||
</dependency>
|
||||
</dependencies>
|
||||
</project>
|
||||
26
jvm-packages/xgboost4j-demo/pom.xml
Normal file
26
jvm-packages/xgboost4j-demo/pom.xml
Normal file
@ -0,0 +1,26 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<project xmlns="http://maven.apache.org/POM/4.0.0"
|
||||
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
|
||||
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
|
||||
<modelVersion>4.0.0</modelVersion>
|
||||
<parent>
|
||||
<groupId>org.dmlc</groupId>
|
||||
<artifactId>xgboostjvm</artifactId>
|
||||
<version>0.1</version>
|
||||
</parent>
|
||||
<artifactId>xgboost4j-demo</artifactId>
|
||||
<version>0.1</version>
|
||||
<packaging>jar</packaging>
|
||||
<dependencies>
|
||||
<dependency>
|
||||
<groupId>org.dmlc</groupId>
|
||||
<artifactId>xgboost4j</artifactId>
|
||||
<version>0.1</version>
|
||||
</dependency>
|
||||
<dependency>
|
||||
<groupId>org.apache.commons</groupId>
|
||||
<artifactId>commons-lang3</artifactId>
|
||||
<version>3.4</version>
|
||||
</dependency>
|
||||
</dependencies>
|
||||
</project>
|
||||
@ -0,0 +1,117 @@
|
||||
/*
|
||||
Copyright (c) 2014 by Contributors
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
*/
|
||||
package org.dmlc.xgboost4j.demo;
|
||||
|
||||
import org.dmlc.xgboost4j.*;
|
||||
import org.dmlc.xgboost4j.demo.util.DataLoader;
|
||||
|
||||
import java.io.File;
|
||||
import java.io.IOException;
|
||||
import java.io.UnsupportedEncodingException;
|
||||
import java.util.Arrays;
|
||||
import java.util.HashMap;
|
||||
|
||||
/**
|
||||
* a simple example of java wrapper for xgboost
|
||||
* @author hzx
|
||||
*/
|
||||
public class BasicWalkThrough {
|
||||
public static boolean checkPredicts(float[][] fPredicts, float[][] sPredicts) {
|
||||
if(fPredicts.length != sPredicts.length) {
|
||||
return false;
|
||||
}
|
||||
|
||||
for(int i=0; i<fPredicts.length; i++) {
|
||||
if(!Arrays.equals(fPredicts[i], sPredicts[i])) {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
return true;
|
||||
}
|
||||
|
||||
|
||||
public static void main(String[] args) throws UnsupportedEncodingException, IOException, XGBoostError {
|
||||
// load file from text file, also binary buffer generated by xgboost4j
|
||||
DMatrix trainMat = new DMatrix("../../demo/data/agaricus.txt.train");
|
||||
DMatrix testMat = new DMatrix("../../demo/data/agaricus.txt.test");
|
||||
|
||||
HashMap<String, Object> params = new HashMap<String, Object>();
|
||||
params.put("eta", 1.0);
|
||||
params.put("max_depth", 2);
|
||||
params.put("silent", 1);
|
||||
params.put("objective", "binary:logistic");
|
||||
|
||||
|
||||
HashMap<String, DMatrix> watches = new HashMap<String, DMatrix>();
|
||||
watches.put("train", trainMat);
|
||||
watches.put("test", testMat);
|
||||
|
||||
//set round
|
||||
int round = 2;
|
||||
|
||||
//train a boost model
|
||||
Booster booster = XGBoost.train(params, trainMat, round, watches, null, null);
|
||||
|
||||
//predict
|
||||
float[][] predicts = booster.predict(testMat);
|
||||
|
||||
//save model to modelPath
|
||||
File file = new File("./model");
|
||||
if(!file.exists()) {
|
||||
file.mkdirs();
|
||||
}
|
||||
|
||||
String modelPath = "./model/xgb.model";
|
||||
booster.saveModel(modelPath);
|
||||
|
||||
//dump model
|
||||
booster.dumpModel("./model/dump.raw.txt", false);
|
||||
|
||||
//dump model with feature map
|
||||
booster.dumpModel("./model/dump.nice.txt", "../../demo/data/featmap.txt", false);
|
||||
|
||||
//save dmatrix into binary buffer
|
||||
testMat.saveBinary("./model/dtest.buffer");
|
||||
|
||||
//reload model and data
|
||||
Booster booster2 = XGBoost.loadBoostModel(params, "./model/xgb.model");
|
||||
DMatrix testMat2 = new DMatrix("./model/dtest.buffer");
|
||||
float[][] predicts2 = booster2.predict(testMat2);
|
||||
|
||||
|
||||
//check the two predicts
|
||||
System.out.println(checkPredicts(predicts, predicts2));
|
||||
|
||||
System.out.println("start build dmatrix from csr sparse data ...");
|
||||
//build dmatrix from CSR Sparse Matrix
|
||||
DataLoader.CSRSparseData spData = DataLoader.loadSVMFile("../../demo/data/agaricus.txt.train");
|
||||
|
||||
DMatrix trainMat2 = new DMatrix(spData.rowHeaders, spData.colIndex, spData.data,
|
||||
DMatrix.SparseType.CSR);
|
||||
trainMat2.setLabel(spData.labels);
|
||||
|
||||
//specify watchList
|
||||
HashMap<String, DMatrix> watches2 = new HashMap<String, DMatrix>();
|
||||
watches2.put("train", trainMat2);
|
||||
watches2.put("test", testMat2);
|
||||
Booster booster3 = XGBoost.train(params, trainMat2, round, watches2, null, null);
|
||||
float[][] predicts3 = booster3.predict(testMat2);
|
||||
|
||||
//check predicts
|
||||
System.out.println(checkPredicts(predicts, predicts3));
|
||||
}
|
||||
}
|
||||
@ -15,15 +15,9 @@
|
||||
*/
|
||||
package org.dmlc.xgboost4j.demo;
|
||||
|
||||
import java.util.AbstractMap;
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
import org.dmlc.xgboost4j.Booster;
|
||||
import org.dmlc.xgboost4j.DMatrix;
|
||||
import org.dmlc.xgboost4j.demo.util.Params;
|
||||
import org.dmlc.xgboost4j.util.Trainer;
|
||||
import org.dmlc.xgboost4j.util.XGBoostError;
|
||||
import org.dmlc.xgboost4j.*;
|
||||
|
||||
import java.util.HashMap;
|
||||
|
||||
/**
|
||||
* example for start from a initial base prediction
|
||||
@ -38,22 +32,19 @@ public class BoostFromPrediction {
|
||||
DMatrix testMat = new DMatrix("../../demo/data/agaricus.txt.test");
|
||||
|
||||
//specify parameters
|
||||
Params param = new Params() {
|
||||
{
|
||||
put("eta", 1.0);
|
||||
put("max_depth", 2);
|
||||
put("silent", 1);
|
||||
put("objective", "binary:logistic");
|
||||
}
|
||||
};
|
||||
HashMap<String, Object> params = new HashMap<String, Object>();
|
||||
params.put("eta", 1.0);
|
||||
params.put("max_depth", 2);
|
||||
params.put("silent", 1);
|
||||
params.put("objective", "binary:logistic");
|
||||
|
||||
//specify watchList
|
||||
List<Map.Entry<String, DMatrix>> watchs = new ArrayList<>();
|
||||
watchs.add(new AbstractMap.SimpleEntry<>("train", trainMat));
|
||||
watchs.add(new AbstractMap.SimpleEntry<>("test", testMat));
|
||||
HashMap<String, DMatrix> watches = new HashMap<String, DMatrix>();
|
||||
watches.put("train", trainMat);
|
||||
watches.put("test", testMat);
|
||||
|
||||
//train xgboost for 1 round
|
||||
Booster booster = Trainer.train(param, trainMat, 1, watchs, null, null);
|
||||
Booster booster = XGBoost.train(params, trainMat, 1, watches, null, null);
|
||||
|
||||
float[][] trainPred = booster.predict(trainMat, true);
|
||||
float[][] testPred = booster.predict(testMat, true);
|
||||
@ -62,6 +53,6 @@ public class BoostFromPrediction {
|
||||
testMat.setBaseMargin(testPred);
|
||||
|
||||
System.out.println("result of running from initial prediction");
|
||||
Booster booster2 = Trainer.train(param, trainMat, 1, watchs, null, null);
|
||||
Booster booster2 = XGBoost.train(params, trainMat, 1, watches, null, null);
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,54 @@
|
||||
/*
|
||||
Copyright (c) 2014 by Contributors
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
*/
|
||||
package org.dmlc.xgboost4j.demo;
|
||||
|
||||
import org.dmlc.xgboost4j.DMatrix;
|
||||
import org.dmlc.xgboost4j.XGBoost;
|
||||
import org.dmlc.xgboost4j.XGBoostError;
|
||||
|
||||
import java.io.IOException;
|
||||
import java.util.HashMap;
|
||||
|
||||
/**
|
||||
* an example of cross validation
|
||||
*
|
||||
* @author hzx
|
||||
*/
|
||||
public class CrossValidation {
|
||||
public static void main(String[] args) throws IOException, XGBoostError {
|
||||
//load train mat
|
||||
DMatrix trainMat = new DMatrix("../../demo/data/agaricus.txt.train");
|
||||
|
||||
//set params
|
||||
HashMap<String, Object> params = new HashMap<String, Object>();
|
||||
|
||||
params.put("eta", 1.0);
|
||||
params.put("max_depth", 3);
|
||||
params.put("silent", 1);
|
||||
params.put("nthread", 6);
|
||||
params.put("objective", "binary:logistic");
|
||||
params.put("gamma", 1.0);
|
||||
params.put("eval_metric", "error");
|
||||
|
||||
//do 5-fold cross validation
|
||||
int round = 2;
|
||||
int nfold = 5;
|
||||
//set additional eval_metrics
|
||||
String[] metrics = null;
|
||||
|
||||
String[] evalHist = XGBoost.crossValiation(params, trainMat, round, nfold, metrics, null, null);
|
||||
}
|
||||
}
|
||||
@ -15,19 +15,13 @@
|
||||
*/
|
||||
package org.dmlc.xgboost4j.demo;
|
||||
|
||||
import java.util.AbstractMap;
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
import org.apache.commons.logging.Log;
|
||||
import org.apache.commons.logging.LogFactory;
|
||||
import org.dmlc.xgboost4j.Booster;
|
||||
import org.dmlc.xgboost4j.IEvaluation;
|
||||
import org.dmlc.xgboost4j.DMatrix;
|
||||
import org.dmlc.xgboost4j.IObjective;
|
||||
import org.dmlc.xgboost4j.demo.util.Params;
|
||||
import org.dmlc.xgboost4j.util.Trainer;
|
||||
import org.dmlc.xgboost4j.util.XGBoostError;
|
||||
import org.dmlc.xgboost4j.*;
|
||||
|
||||
import java.util.ArrayList;
|
||||
import java.util.HashMap;
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* an example user define objective and eval
|
||||
@ -68,9 +62,9 @@ public class CustomObjective {
|
||||
}
|
||||
|
||||
@Override
|
||||
public List<float[]> getGradient(float[][] predicts, DMatrix dtrain) {
|
||||
public List<float[]> getGradient(float[][] predicts, org.dmlc.xgboost4j.DMatrix dtrain) {
|
||||
int nrow = predicts.length;
|
||||
List<float[]> gradients = new ArrayList<>();
|
||||
List<float[]> gradients = new ArrayList<float[]>();
|
||||
float[] labels;
|
||||
try {
|
||||
labels = dtrain.getLabel();
|
||||
@ -117,7 +111,7 @@ public class CustomObjective {
|
||||
}
|
||||
|
||||
@Override
|
||||
public float eval(float[][] predicts, DMatrix dmat) {
|
||||
public float eval(float[][] predicts, org.dmlc.xgboost4j.DMatrix dmat) {
|
||||
float error = 0f;
|
||||
float[] labels;
|
||||
try {
|
||||
@ -142,34 +136,30 @@ public class CustomObjective {
|
||||
|
||||
public static void main(String[] args) throws XGBoostError {
|
||||
//load train mat (svmlight format)
|
||||
DMatrix trainMat = new DMatrix("../../demo/data/agaricus.txt.train");
|
||||
org.dmlc.xgboost4j.DMatrix trainMat = new org.dmlc.xgboost4j.DMatrix("../../demo/data/agaricus.txt.train");
|
||||
//load valid mat (svmlight format)
|
||||
DMatrix testMat = new DMatrix("../../demo/data/agaricus.txt.test");
|
||||
org.dmlc.xgboost4j.DMatrix testMat = new org.dmlc.xgboost4j.DMatrix("../../demo/data/agaricus.txt.test");
|
||||
|
||||
//set params
|
||||
//set params
|
||||
Params param = new Params() {
|
||||
{
|
||||
put("eta", 1.0);
|
||||
put("max_depth", 2);
|
||||
put("silent", 1);
|
||||
}
|
||||
};
|
||||
HashMap<String, Object> params = new HashMap<String, Object>();
|
||||
params.put("eta", 1.0);
|
||||
params.put("max_depth", 2);
|
||||
params.put("silent", 1);
|
||||
|
||||
|
||||
//set round
|
||||
int round = 2;
|
||||
|
||||
//specify watchList
|
||||
List<Map.Entry<String, DMatrix>> watchs = new ArrayList<>();
|
||||
watchs.add(new AbstractMap.SimpleEntry<>("train", trainMat));
|
||||
watchs.add(new AbstractMap.SimpleEntry<>("test", testMat));
|
||||
HashMap<String, org.dmlc.xgboost4j.DMatrix> watches = new HashMap<String, org.dmlc.xgboost4j.DMatrix>();
|
||||
watches.put("train", trainMat);
|
||||
watches.put("test", testMat);
|
||||
|
||||
//user define obj and eval
|
||||
IObjective obj = new LogRegObj();
|
||||
IEvaluation eval = new EvalError();
|
||||
|
||||
//train a booster
|
||||
System.out.println("begin to train the booster model");
|
||||
Booster booster = Trainer.train(param, trainMat, round, watchs, obj, eval);
|
||||
System.out.println("begin to train the booster model");
|
||||
Booster booster = XGBoost.train(params, trainMat, round, watches, obj, eval);
|
||||
}
|
||||
}
|
||||
@ -15,15 +15,9 @@
|
||||
*/
|
||||
package org.dmlc.xgboost4j.demo;
|
||||
|
||||
import java.util.AbstractMap;
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
import org.dmlc.xgboost4j.Booster;
|
||||
import org.dmlc.xgboost4j.DMatrix;
|
||||
import org.dmlc.xgboost4j.demo.util.Params;
|
||||
import org.dmlc.xgboost4j.util.Trainer;
|
||||
import org.dmlc.xgboost4j.util.XGBoostError;
|
||||
import org.dmlc.xgboost4j.*;
|
||||
|
||||
import java.util.HashMap;
|
||||
|
||||
/**
|
||||
* simple example for using external memory version
|
||||
@ -38,28 +32,25 @@ public class ExternalMemory {
|
||||
DMatrix testMat = new DMatrix("../../demo/data/agaricus.txt.test#dtest.cache");
|
||||
|
||||
//specify parameters
|
||||
Params param = new Params() {
|
||||
{
|
||||
put("eta", 1.0);
|
||||
put("max_depth", 2);
|
||||
put("silent", 1);
|
||||
put("objective", "binary:logistic");
|
||||
}
|
||||
};
|
||||
HashMap<String, Object> params = new HashMap<String, Object>();
|
||||
params.put("eta", 1.0);
|
||||
params.put("max_depth", 2);
|
||||
params.put("silent", 1);
|
||||
params.put("objective", "binary:logistic");
|
||||
|
||||
//performance notice: set nthread to be the number of your real cpu
|
||||
//some cpu offer two threads per core, for example, a 4 core cpu with 8 threads, in such case set nthread=4
|
||||
//param.put("nthread", num_real_cpu);
|
||||
|
||||
//specify watchList
|
||||
List<Map.Entry<String, DMatrix>> watchs = new ArrayList<>();
|
||||
watchs.add(new AbstractMap.SimpleEntry<>("train", trainMat));
|
||||
watchs.add(new AbstractMap.SimpleEntry<>("test", testMat));
|
||||
HashMap<String, DMatrix> watches = new HashMap<String, DMatrix>();
|
||||
watches.put("train", trainMat);
|
||||
watches.put("test", testMat);
|
||||
|
||||
//set round
|
||||
int round = 2;
|
||||
|
||||
//train a boost model
|
||||
Booster booster = Trainer.train(param, trainMat, round, watchs, null, null);
|
||||
Booster booster = XGBoost.train(params, trainMat, round, watches, null, null);
|
||||
}
|
||||
}
|
||||
@ -15,16 +15,10 @@
|
||||
*/
|
||||
package org.dmlc.xgboost4j.demo;
|
||||
|
||||
import java.util.AbstractMap;
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
import org.dmlc.xgboost4j.Booster;
|
||||
import org.dmlc.xgboost4j.DMatrix;
|
||||
import org.dmlc.xgboost4j.*;
|
||||
import org.dmlc.xgboost4j.demo.util.CustomEval;
|
||||
import org.dmlc.xgboost4j.demo.util.Params;
|
||||
import org.dmlc.xgboost4j.util.Trainer;
|
||||
import org.dmlc.xgboost4j.util.XGBoostError;
|
||||
|
||||
import java.util.HashMap;
|
||||
|
||||
/**
|
||||
* this is an example of fit generalized linear model in xgboost
|
||||
@ -42,14 +36,12 @@ public class GeneralizedLinearModel {
|
||||
// alpha is the L1 regularizer
|
||||
//lambda is the L2 regularizer
|
||||
//you can also set lambda_bias which is L2 regularizer on the bias term
|
||||
Params param = new Params() {
|
||||
{
|
||||
put("alpha", 0.0001);
|
||||
put("silent", 1);
|
||||
put("objective", "binary:logistic");
|
||||
put("booster", "gblinear");
|
||||
}
|
||||
};
|
||||
HashMap<String, Object> params = new HashMap<String, Object>();
|
||||
params.put("alpha", 0.0001);
|
||||
params.put("silent", 1);
|
||||
params.put("objective", "binary:logistic");
|
||||
params.put("booster", "gblinear");
|
||||
|
||||
//normally, you do not need to set eta (step_size)
|
||||
//XGBoost uses a parallel coordinate descent algorithm (shotgun),
|
||||
//there could be affection on convergence with parallelization on certain cases
|
||||
@ -58,13 +50,13 @@ public class GeneralizedLinearModel {
|
||||
|
||||
|
||||
//specify watchList
|
||||
List<Map.Entry<String, DMatrix>> watchs = new ArrayList<>();
|
||||
watchs.add(new AbstractMap.SimpleEntry<>("train", trainMat));
|
||||
watchs.add(new AbstractMap.SimpleEntry<>("test", testMat));
|
||||
HashMap<String, DMatrix> watches = new HashMap<String, DMatrix>();
|
||||
watches.put("train", trainMat);
|
||||
watches.put("test", testMat);
|
||||
|
||||
//train a booster
|
||||
int round = 4;
|
||||
Booster booster = Trainer.train(param, trainMat, round, watchs, null, null);
|
||||
Booster booster = XGBoost.train(params, trainMat, round, watches, null, null);
|
||||
|
||||
float[][] predicts = booster.predict(testMat);
|
||||
|
||||
@ -15,17 +15,10 @@
|
||||
*/
|
||||
package org.dmlc.xgboost4j.demo;
|
||||
|
||||
import java.util.AbstractMap;
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
import org.dmlc.xgboost4j.Booster;
|
||||
import org.dmlc.xgboost4j.DMatrix;
|
||||
import org.dmlc.xgboost4j.util.Trainer;
|
||||
|
||||
import org.dmlc.xgboost4j.*;
|
||||
import org.dmlc.xgboost4j.demo.util.CustomEval;
|
||||
import org.dmlc.xgboost4j.demo.util.Params;
|
||||
import org.dmlc.xgboost4j.util.XGBoostError;
|
||||
|
||||
import java.util.HashMap;
|
||||
|
||||
/**
|
||||
* predict first ntree
|
||||
@ -38,23 +31,23 @@ public class PredictFirstNtree {
|
||||
DMatrix testMat = new DMatrix("../../demo/data/agaricus.txt.test");
|
||||
|
||||
//specify parameters
|
||||
Params param = new Params() {
|
||||
{
|
||||
put("eta", 1.0);
|
||||
put("max_depth", 2);
|
||||
put("silent", 1);
|
||||
put("objective", "binary:logistic");
|
||||
}
|
||||
};
|
||||
HashMap<String, Object> params = new HashMap<String, Object>();
|
||||
|
||||
params.put("eta", 1.0);
|
||||
params.put("max_depth", 2);
|
||||
params.put("silent", 1);
|
||||
params.put("objective", "binary:logistic");
|
||||
|
||||
|
||||
//specify watchList
|
||||
List<Map.Entry<String, DMatrix>> watchs = new ArrayList<>();
|
||||
watchs.add(new AbstractMap.SimpleEntry<>("train", trainMat));
|
||||
watchs.add(new AbstractMap.SimpleEntry<>("test", testMat));
|
||||
HashMap<String, DMatrix> watches = new HashMap<String, DMatrix>();
|
||||
watches.put("train", trainMat);
|
||||
watches.put("test", testMat);
|
||||
|
||||
|
||||
//train a booster
|
||||
int round = 3;
|
||||
Booster booster = Trainer.train(param, trainMat, round, watchs, null, null);
|
||||
Booster booster = XGBoost.train(params, trainMat, round, watches, null, null);
|
||||
|
||||
//predict use 1 tree
|
||||
float[][] predicts1 = booster.predict(testMat, false, 1);
|
||||
@ -15,16 +15,10 @@
|
||||
*/
|
||||
package org.dmlc.xgboost4j.demo;
|
||||
|
||||
import java.util.AbstractMap;
|
||||
import java.util.ArrayList;
|
||||
import org.dmlc.xgboost4j.*;
|
||||
|
||||
import java.util.Arrays;
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
import org.dmlc.xgboost4j.Booster;
|
||||
import org.dmlc.xgboost4j.DMatrix;
|
||||
import org.dmlc.xgboost4j.util.Trainer;
|
||||
import org.dmlc.xgboost4j.demo.util.Params;
|
||||
import org.dmlc.xgboost4j.util.XGBoostError;
|
||||
import java.util.HashMap;
|
||||
|
||||
/**
|
||||
* predict leaf indices
|
||||
@ -37,23 +31,21 @@ public class PredictLeafIndices {
|
||||
DMatrix testMat = new DMatrix("../../demo/data/agaricus.txt.test");
|
||||
|
||||
//specify parameters
|
||||
Params param = new Params() {
|
||||
{
|
||||
put("eta", 1.0);
|
||||
put("max_depth", 2);
|
||||
put("silent", 1);
|
||||
put("objective", "binary:logistic");
|
||||
}
|
||||
};
|
||||
HashMap<String, Object> params = new HashMap<String, Object>();
|
||||
params.put("eta", 1.0);
|
||||
params.put("max_depth", 2);
|
||||
params.put("silent", 1);
|
||||
params.put("objective", "binary:logistic");
|
||||
|
||||
//specify watchList
|
||||
List<Map.Entry<String, DMatrix>> watchs = new ArrayList<>();
|
||||
watchs.add(new AbstractMap.SimpleEntry<>("train", trainMat));
|
||||
watchs.add(new AbstractMap.SimpleEntry<>("test", testMat));
|
||||
HashMap<String, DMatrix> watches = new HashMap<String, DMatrix>();
|
||||
watches.put("train", trainMat);
|
||||
watches.put("test", testMat);
|
||||
|
||||
|
||||
//train a booster
|
||||
int round = 3;
|
||||
Booster booster = Trainer.train(param, trainMat, round, watchs, null, null);
|
||||
Booster booster = XGBoost.train(params, trainMat, round, watches, null, null);
|
||||
|
||||
//predict using first 2 tree
|
||||
float[][] leafindex = booster.predict(testMat, 2, true);
|
||||
@ -19,7 +19,7 @@ import org.apache.commons.logging.Log;
|
||||
import org.apache.commons.logging.LogFactory;
|
||||
import org.dmlc.xgboost4j.DMatrix;
|
||||
import org.dmlc.xgboost4j.IEvaluation;
|
||||
import org.dmlc.xgboost4j.util.XGBoostError;
|
||||
import org.dmlc.xgboost4j.XGBoostError;
|
||||
|
||||
/**
|
||||
* a util evaluation class for examples
|
||||
@ -15,16 +15,11 @@
|
||||
*/
|
||||
package org.dmlc.xgboost4j.demo.util;
|
||||
|
||||
import java.io.BufferedReader;
|
||||
import java.io.File;
|
||||
import java.io.FileInputStream;
|
||||
import java.io.FileNotFoundException;
|
||||
import java.io.IOException;
|
||||
import java.io.InputStreamReader;
|
||||
import java.io.UnsupportedEncodingException;
|
||||
import org.apache.commons.lang3.ArrayUtils;
|
||||
|
||||
import java.io.*;
|
||||
import java.util.ArrayList;
|
||||
import java.util.List;
|
||||
import org.apache.commons.lang3.ArrayUtils;
|
||||
|
||||
/**
|
||||
* util class for loading data
|
||||
35
jvm-packages/xgboost4j/pom.xml
Normal file
35
jvm-packages/xgboost4j/pom.xml
Normal file
@ -0,0 +1,35 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<project xmlns="http://maven.apache.org/POM/4.0.0"
|
||||
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
|
||||
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
|
||||
<modelVersion>4.0.0</modelVersion>
|
||||
<parent>
|
||||
<groupId>org.dmlc</groupId>
|
||||
<artifactId>xgboostjvm</artifactId>
|
||||
<version>0.1</version>
|
||||
</parent>
|
||||
<artifactId>xgboost4j</artifactId>
|
||||
<version>0.1</version>
|
||||
<packaging>jar</packaging>
|
||||
<build>
|
||||
<plugins>
|
||||
<plugin>
|
||||
<groupId>org.apache.maven.plugins</groupId>
|
||||
<artifactId>maven-javadoc-plugin</artifactId>
|
||||
<version>2.10.3</version>
|
||||
<configuration>
|
||||
<show>protected</show>
|
||||
<nohelp>true</nohelp>
|
||||
</configuration>
|
||||
</plugin>
|
||||
</plugins>
|
||||
</build>
|
||||
<dependencies>
|
||||
<dependency>
|
||||
<groupId>junit</groupId>
|
||||
<artifactId>junit</artifactId>
|
||||
<version>4.11</version>
|
||||
<scope>test</scope>
|
||||
</dependency>
|
||||
</dependencies>
|
||||
</project>
|
||||
@ -0,0 +1,152 @@
|
||||
package org.dmlc.xgboost4j;
|
||||
|
||||
import java.io.IOException;
|
||||
import java.util.Map;
|
||||
|
||||
public interface Booster {
|
||||
|
||||
/**
|
||||
* set parameter
|
||||
*
|
||||
* @param key param name
|
||||
* @param value param value
|
||||
*/
|
||||
void setParam(String key, String value) throws XGBoostError;
|
||||
|
||||
/**
|
||||
* set parameters
|
||||
*
|
||||
* @param params parameters key-value map
|
||||
*/
|
||||
void setParams(Map<String, Object> params) throws XGBoostError;
|
||||
|
||||
/**
|
||||
* Update (one iteration)
|
||||
*
|
||||
* @param dtrain training data
|
||||
* @param iter current iteration number
|
||||
*/
|
||||
void update(DMatrix dtrain, int iter) throws XGBoostError;
|
||||
|
||||
/**
|
||||
* update with customize obj func
|
||||
*
|
||||
* @param dtrain training data
|
||||
* @param obj customized objective class
|
||||
*/
|
||||
void update(DMatrix dtrain, IObjective obj) throws XGBoostError;
|
||||
|
||||
/**
|
||||
* update with give grad and hess
|
||||
*
|
||||
* @param dtrain training data
|
||||
* @param grad first order of gradient
|
||||
* @param hess seconde order of gradient
|
||||
*/
|
||||
void boost(DMatrix dtrain, float[] grad, float[] hess) throws XGBoostError;
|
||||
|
||||
/**
|
||||
* evaluate with given dmatrixs.
|
||||
*
|
||||
* @param evalMatrixs dmatrixs for evaluation
|
||||
* @param evalNames name for eval dmatrixs, used for check results
|
||||
* @param iter current eval iteration
|
||||
* @return eval information
|
||||
*/
|
||||
String evalSet(DMatrix[] evalMatrixs, String[] evalNames, int iter) throws XGBoostError;
|
||||
|
||||
/**
|
||||
* evaluate with given customized Evaluation class
|
||||
*
|
||||
* @param evalMatrixs evaluation matrix
|
||||
* @param evalNames evaluation names
|
||||
* @param eval custom evaluator
|
||||
* @return eval information
|
||||
*/
|
||||
String evalSet(DMatrix[] evalMatrixs, String[] evalNames, IEvaluation eval) throws XGBoostError;
|
||||
|
||||
/**
|
||||
* Predict with data
|
||||
*
|
||||
* @param data dmatrix storing the input
|
||||
* @return predict result
|
||||
*/
|
||||
float[][] predict(DMatrix data) throws XGBoostError;
|
||||
|
||||
|
||||
/**
|
||||
* Predict with data
|
||||
*
|
||||
* @param data dmatrix storing the input
|
||||
* @param outPutMargin Whether to output the raw untransformed margin value.
|
||||
* @return predict result
|
||||
*/
|
||||
float[][] predict(DMatrix data, boolean outPutMargin) throws XGBoostError;
|
||||
|
||||
|
||||
/**
|
||||
* Predict with data
|
||||
*
|
||||
* @param data dmatrix storing the input
|
||||
* @param outPutMargin Whether to output the raw untransformed margin value.
|
||||
* @param treeLimit Limit number of trees in the prediction; defaults to 0 (use all trees).
|
||||
* @return predict result
|
||||
*/
|
||||
float[][] predict(DMatrix data, boolean outPutMargin, int treeLimit) throws XGBoostError;
|
||||
|
||||
|
||||
/**
|
||||
* Predict with data
|
||||
* @param data dmatrix storing the input
|
||||
* @param treeLimit Limit number of trees in the prediction; defaults to 0 (use all trees).
|
||||
* @param predLeaf When this option is on, the output will be a matrix of (nsample, ntrees), nsample = data.numRow
|
||||
with each record indicating the predicted leaf index of each sample in each tree.
|
||||
Note that the leaf index of a tree is unique per tree, so you may find leaf 1
|
||||
in both tree 1 and tree 0.
|
||||
* @return predict result
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
float[][] predict(DMatrix data, int treeLimit, boolean predLeaf) throws XGBoostError;
|
||||
|
||||
/**
|
||||
* save model to modelPath
|
||||
*
|
||||
* @param modelPath model path
|
||||
*/
|
||||
void saveModel(String modelPath) throws XGBoostError;
|
||||
|
||||
/**
|
||||
* Dump model into a text file.
|
||||
*
|
||||
* @param modelPath file to save dumped model info
|
||||
* @param withStats bool Controls whether the split statistics are output.
|
||||
*/
|
||||
void dumpModel(String modelPath, boolean withStats) throws IOException, XGBoostError;
|
||||
|
||||
/**
|
||||
* Dump model into a text file.
|
||||
*
|
||||
* @param modelPath file to save dumped model info
|
||||
* @param featureMap featureMap file
|
||||
* @param withStats bool
|
||||
* Controls whether the split statistics are output.
|
||||
*/
|
||||
void dumpModel(String modelPath, String featureMap, boolean withStats) throws IOException, XGBoostError;
|
||||
|
||||
/**
|
||||
* get importance of each feature
|
||||
*
|
||||
* @return featureMap key: feature index, value: feature importance score
|
||||
*/
|
||||
Map<String, Integer> getFeatureScore() throws XGBoostError ;
|
||||
|
||||
/**
|
||||
* get importance of each feature
|
||||
*
|
||||
* @param featureMap file to save dumped model info
|
||||
* @return featureMap key: feature index, value: feature importance score
|
||||
*/
|
||||
Map<String, Integer> getFeatureScore(String featureMap) throws XGBoostError;
|
||||
|
||||
void dispose();
|
||||
}
|
||||
@ -0,0 +1,265 @@
|
||||
/*
|
||||
Copyright (c) 2014 by Contributors
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
*/
|
||||
package org.dmlc.xgboost4j;
|
||||
|
||||
import org.apache.commons.logging.Log;
|
||||
import org.apache.commons.logging.LogFactory;
|
||||
|
||||
import java.io.IOException;
|
||||
|
||||
/**
|
||||
* DMatrix for xgboost, similar to the python wrapper xgboost.py
|
||||
*
|
||||
* @author hzx
|
||||
*/
|
||||
public class DMatrix {
|
||||
private static final Log logger = LogFactory.getLog(DMatrix.class);
|
||||
private long handle = 0;
|
||||
|
||||
//load native library
|
||||
static {
|
||||
try {
|
||||
NativeLibLoader.InitXgboost();
|
||||
} catch (IOException ex) {
|
||||
logger.error("load native library failed.");
|
||||
logger.error(ex);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* sparse matrix type (CSR or CSC)
|
||||
*/
|
||||
public static enum SparseType {
|
||||
CSR,
|
||||
CSC;
|
||||
}
|
||||
|
||||
public DMatrix(String dataPath) throws XGBoostError {
|
||||
if (dataPath == null) {
|
||||
throw new NullPointerException("dataPath: null");
|
||||
}
|
||||
long[] out = new long[1];
|
||||
JNIErrorHandle.checkCall(XgboostJNI.XGDMatrixCreateFromFile(dataPath, 1, out));
|
||||
handle = out[0];
|
||||
}
|
||||
|
||||
public DMatrix(long[] headers, int[] indices, float[] data, SparseType st) throws XGBoostError {
|
||||
long[] out = new long[1];
|
||||
if (st == SparseType.CSR) {
|
||||
JNIErrorHandle.checkCall(XgboostJNI.XGDMatrixCreateFromCSR(headers, indices, data, out));
|
||||
} else if (st == SparseType.CSC) {
|
||||
JNIErrorHandle.checkCall(XgboostJNI.XGDMatrixCreateFromCSC(headers, indices, data, out));
|
||||
} else {
|
||||
throw new UnknownError("unknow sparsetype");
|
||||
}
|
||||
handle = out[0];
|
||||
}
|
||||
|
||||
/**
|
||||
* create DMatrix from dense matrix
|
||||
*
|
||||
* @param data data values
|
||||
* @param nrow number of rows
|
||||
* @param ncol number of columns
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public DMatrix(float[] data, int nrow, int ncol) throws XGBoostError {
|
||||
long[] out = new long[1];
|
||||
JNIErrorHandle.checkCall(XgboostJNI.XGDMatrixCreateFromMat(data, nrow, ncol, 0.0f, out));
|
||||
handle = out[0];
|
||||
}
|
||||
|
||||
/**
|
||||
* used for DMatrix slice
|
||||
*
|
||||
* @param handle
|
||||
*/
|
||||
protected DMatrix(long handle) {
|
||||
this.handle = handle;
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* set label of dmatrix
|
||||
*
|
||||
* @param labels labels
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public void setLabel(float[] labels) throws XGBoostError {
|
||||
JNIErrorHandle.checkCall(XgboostJNI.XGDMatrixSetFloatInfo(handle, "label", labels));
|
||||
}
|
||||
|
||||
/**
|
||||
* set weight of each instance
|
||||
*
|
||||
* @param weights weights
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public void setWeight(float[] weights) throws XGBoostError {
|
||||
JNIErrorHandle.checkCall(XgboostJNI.XGDMatrixSetFloatInfo(handle, "weight", weights));
|
||||
}
|
||||
|
||||
/**
|
||||
* if specified, xgboost will start from this init margin
|
||||
* can be used to specify initial prediction to boost from
|
||||
*
|
||||
* @param baseMargin base margin
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public void setBaseMargin(float[] baseMargin) throws XGBoostError {
|
||||
JNIErrorHandle.checkCall(XgboostJNI.XGDMatrixSetFloatInfo(handle, "base_margin", baseMargin));
|
||||
}
|
||||
|
||||
/**
|
||||
* if specified, xgboost will start from this init margin
|
||||
* can be used to specify initial prediction to boost from
|
||||
*
|
||||
* @param baseMargin base margin
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public void setBaseMargin(float[][] baseMargin) throws XGBoostError {
|
||||
float[] flattenMargin = flatten(baseMargin);
|
||||
setBaseMargin(flattenMargin);
|
||||
}
|
||||
|
||||
/**
|
||||
* Set group sizes of DMatrix (used for ranking)
|
||||
*
|
||||
* @param group group size as array
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public void setGroup(int[] group) throws XGBoostError {
|
||||
JNIErrorHandle.checkCall(XgboostJNI.XGDMatrixSetGroup(handle, group));
|
||||
}
|
||||
|
||||
private float[] getFloatInfo(String field) throws XGBoostError {
|
||||
float[][] infos = new float[1][];
|
||||
JNIErrorHandle.checkCall(XgboostJNI.XGDMatrixGetFloatInfo(handle, field, infos));
|
||||
return infos[0];
|
||||
}
|
||||
|
||||
private int[] getIntInfo(String field) throws XGBoostError {
|
||||
int[][] infos = new int[1][];
|
||||
JNIErrorHandle.checkCall(XgboostJNI.XGDMatrixGetUIntInfo(handle, field, infos));
|
||||
return infos[0];
|
||||
}
|
||||
|
||||
/**
|
||||
* get label values
|
||||
*
|
||||
* @return label
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public float[] getLabel() throws XGBoostError {
|
||||
return getFloatInfo("label");
|
||||
}
|
||||
|
||||
/**
|
||||
* get weight of the DMatrix
|
||||
*
|
||||
* @return weights
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public float[] getWeight() throws XGBoostError {
|
||||
return getFloatInfo("weight");
|
||||
}
|
||||
|
||||
/**
|
||||
* get base margin of the DMatrix
|
||||
*
|
||||
* @return base margin
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public float[] getBaseMargin() throws XGBoostError {
|
||||
return getFloatInfo("base_margin");
|
||||
}
|
||||
|
||||
/**
|
||||
* Slice the DMatrix and return a new DMatrix that only contains `rowIndex`.
|
||||
*
|
||||
* @param rowIndex row index
|
||||
* @return sliced new DMatrix
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public DMatrix slice(int[] rowIndex) throws XGBoostError {
|
||||
long[] out = new long[1];
|
||||
JNIErrorHandle.checkCall(XgboostJNI.XGDMatrixSliceDMatrix(handle, rowIndex, out));
|
||||
long sHandle = out[0];
|
||||
DMatrix sMatrix = new DMatrix(sHandle);
|
||||
return sMatrix;
|
||||
}
|
||||
|
||||
/**
|
||||
* get the row number of DMatrix
|
||||
*
|
||||
* @return number of rows
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public long rowNum() throws XGBoostError {
|
||||
long[] rowNum = new long[1];
|
||||
JNIErrorHandle.checkCall(XgboostJNI.XGDMatrixNumRow(handle, rowNum));
|
||||
return rowNum[0];
|
||||
}
|
||||
|
||||
/**
|
||||
* save DMatrix to filePath
|
||||
*
|
||||
* @param filePath file path
|
||||
*/
|
||||
public void saveBinary(String filePath) {
|
||||
XgboostJNI.XGDMatrixSaveBinary(handle, filePath, 1);
|
||||
}
|
||||
|
||||
/**
|
||||
* Get the handle
|
||||
*
|
||||
* @return native handler id
|
||||
*/
|
||||
public long getHandle() {
|
||||
return handle;
|
||||
}
|
||||
|
||||
/**
|
||||
* flatten a mat to array
|
||||
*
|
||||
* @param mat
|
||||
* @return
|
||||
*/
|
||||
private static float[] flatten(float[][] mat) {
|
||||
int size = 0;
|
||||
for (float[] array : mat) size += array.length;
|
||||
float[] result = new float[size];
|
||||
int pos = 0;
|
||||
for (float[] ar : mat) {
|
||||
System.arraycopy(ar, 0, result, pos, ar.length);
|
||||
pos += ar.length;
|
||||
}
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
@Override
|
||||
protected void finalize() {
|
||||
dispose();
|
||||
}
|
||||
|
||||
public synchronized void dispose() {
|
||||
if (handle != 0) {
|
||||
XgboostJNI.XGDMatrixFree(handle);
|
||||
handle = 0;
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -17,25 +17,23 @@ package org.dmlc.xgboost4j;
|
||||
|
||||
/**
|
||||
* interface for customized evaluation
|
||||
*
|
||||
*
|
||||
* @author hzx
|
||||
*/
|
||||
public interface IEvaluation {
|
||||
/**
|
||||
* get evaluate metric
|
||||
*
|
||||
* @return evalMetric
|
||||
*/
|
||||
public abstract String getMetric();
|
||||
/**
|
||||
* get evaluate metric
|
||||
*
|
||||
* @return evalMetric
|
||||
*/
|
||||
String getMetric();
|
||||
|
||||
/**
|
||||
* evaluate with predicts and data
|
||||
*
|
||||
* @param predicts
|
||||
* predictions as array
|
||||
* @param dmat
|
||||
* data matrix to evaluate
|
||||
* @return result of the metric
|
||||
*/
|
||||
public abstract float eval(float[][] predicts, DMatrix dmat);
|
||||
/**
|
||||
* evaluate with predicts and data
|
||||
*
|
||||
* @param predicts predictions as array
|
||||
* @param dmat data matrix to evaluate
|
||||
* @return result of the metric
|
||||
*/
|
||||
float eval(float[][] predicts, DMatrix dmat);
|
||||
}
|
||||
@ -19,14 +19,16 @@ import java.util.List;
|
||||
|
||||
/**
|
||||
* interface for customize Object function
|
||||
*
|
||||
* @author hzx
|
||||
*/
|
||||
public interface IObjective {
|
||||
/**
|
||||
* user define objective function, return gradient and second order gradient
|
||||
* @param predicts untransformed margin predicts
|
||||
* @param dtrain training data
|
||||
* @return List with two float array, correspond to first order grad and second order grad
|
||||
*/
|
||||
public abstract List<float[]> getGradient(float[][] predicts, DMatrix dtrain);
|
||||
/**
|
||||
* user define objective function, return gradient and second order gradient
|
||||
*
|
||||
* @param predicts untransformed margin predicts
|
||||
* @param dtrain training data
|
||||
* @return List with two float array, correspond to first order grad and second order grad
|
||||
*/
|
||||
List<float[]> getGradient(float[][] predicts, DMatrix dtrain);
|
||||
}
|
||||
@ -0,0 +1,51 @@
|
||||
/*
|
||||
Copyright (c) 2014 by Contributors
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
*/
|
||||
package org.dmlc.xgboost4j;
|
||||
|
||||
import org.apache.commons.logging.Log;
|
||||
import org.apache.commons.logging.LogFactory;
|
||||
|
||||
import java.io.IOException;
|
||||
|
||||
/**
|
||||
* Error handle for Xgboost.
|
||||
*/
|
||||
class JNIErrorHandle {
|
||||
|
||||
private static final Log logger = LogFactory.getLog(DMatrix.class);
|
||||
|
||||
//load native library
|
||||
static {
|
||||
try {
|
||||
NativeLibLoader.InitXgboost();
|
||||
} catch (IOException ex) {
|
||||
logger.error("load native library failed.");
|
||||
logger.error(ex);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Check the return value of C API.
|
||||
*
|
||||
* @param ret return valud of xgboostJNI C API call
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
static void checkCall(int ret) throws XGBoostError {
|
||||
if (ret != 0) {
|
||||
throw new XGBoostError(XgboostJNI.XGBGetLastError());
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,467 @@
|
||||
/*
|
||||
Copyright (c) 2014 by Contributors
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
*/
|
||||
package org.dmlc.xgboost4j;
|
||||
|
||||
import org.apache.commons.logging.Log;
|
||||
import org.apache.commons.logging.LogFactory;
|
||||
|
||||
import java.io.*;
|
||||
import java.util.HashMap;
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
|
||||
|
||||
/**
|
||||
* Booster for xgboost, similar to the python wrapper xgboost.py
|
||||
* but custom obj function and eval function not supported at present.
|
||||
*
|
||||
* @author hzx
|
||||
*/
|
||||
class JavaBoosterImpl implements Booster {
|
||||
private static final Log logger = LogFactory.getLog(JavaBoosterImpl.class);
|
||||
|
||||
long handle = 0;
|
||||
|
||||
//load native library
|
||||
static {
|
||||
try {
|
||||
NativeLibLoader.InitXgboost();
|
||||
} catch (IOException ex) {
|
||||
logger.error("load native library failed.");
|
||||
logger.error(ex);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* init Booster from dMatrixs
|
||||
*
|
||||
* @param params parameters
|
||||
* @param dMatrixs DMatrix array
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
JavaBoosterImpl(Map<String, Object> params, DMatrix[] dMatrixs) throws XGBoostError {
|
||||
init(dMatrixs);
|
||||
setParam("seed", "0");
|
||||
setParams(params);
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* load model from modelPath
|
||||
*
|
||||
* @param params parameters
|
||||
* @param modelPath booster modelPath (model generated by booster.saveModel)
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
JavaBoosterImpl(Map<String, Object> params, String modelPath) throws XGBoostError {
|
||||
init(null);
|
||||
if (modelPath == null) {
|
||||
throw new NullPointerException("modelPath : null");
|
||||
}
|
||||
loadModel(modelPath);
|
||||
setParam("seed", "0");
|
||||
setParams(params);
|
||||
}
|
||||
|
||||
|
||||
private void init(DMatrix[] dMatrixs) throws XGBoostError {
|
||||
long[] handles = null;
|
||||
if (dMatrixs != null) {
|
||||
handles = dMatrixs2handles(dMatrixs);
|
||||
}
|
||||
long[] out = new long[1];
|
||||
JNIErrorHandle.checkCall(XgboostJNI.XGBoosterCreate(handles, out));
|
||||
|
||||
handle = out[0];
|
||||
}
|
||||
|
||||
/**
|
||||
* set parameter
|
||||
*
|
||||
* @param key param name
|
||||
* @param value param value
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public final void setParam(String key, String value) throws XGBoostError {
|
||||
JNIErrorHandle.checkCall(XgboostJNI.XGBoosterSetParam(handle, key, value));
|
||||
}
|
||||
|
||||
/**
|
||||
* set parameters
|
||||
*
|
||||
* @param params parameters key-value map
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public void setParams(Map<String, Object> params) throws XGBoostError {
|
||||
if (params != null) {
|
||||
for (Map.Entry<String, Object> entry : params.entrySet()) {
|
||||
setParam(entry.getKey(), entry.getValue().toString());
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* Update (one iteration)
|
||||
*
|
||||
* @param dtrain training data
|
||||
* @param iter current iteration number
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public void update(DMatrix dtrain, int iter) throws XGBoostError {
|
||||
JNIErrorHandle.checkCall(XgboostJNI.XGBoosterUpdateOneIter(handle, iter, dtrain.getHandle()));
|
||||
}
|
||||
|
||||
/**
|
||||
* update with customize obj func
|
||||
*
|
||||
* @param dtrain training data
|
||||
* @param obj customized objective class
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public void update(DMatrix dtrain, IObjective obj) throws XGBoostError {
|
||||
float[][] predicts = predict(dtrain, true);
|
||||
List<float[]> gradients = obj.getGradient(predicts, dtrain);
|
||||
boost(dtrain, gradients.get(0), gradients.get(1));
|
||||
}
|
||||
|
||||
/**
|
||||
* update with give grad and hess
|
||||
*
|
||||
* @param dtrain training data
|
||||
* @param grad first order of gradient
|
||||
* @param hess seconde order of gradient
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public void boost(DMatrix dtrain, float[] grad, float[] hess) throws XGBoostError {
|
||||
if (grad.length != hess.length) {
|
||||
throw new AssertionError(String.format("grad/hess length mismatch %s / %s", grad.length,
|
||||
hess.length));
|
||||
}
|
||||
JNIErrorHandle.checkCall(XgboostJNI.XGBoosterBoostOneIter(handle, dtrain.getHandle(), grad, hess));
|
||||
}
|
||||
|
||||
/**
|
||||
* evaluate with given dmatrixs.
|
||||
*
|
||||
* @param evalMatrixs dmatrixs for evaluation
|
||||
* @param evalNames name for eval dmatrixs, used for check results
|
||||
* @param iter current eval iteration
|
||||
* @return eval information
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public String evalSet(DMatrix[] evalMatrixs, String[] evalNames, int iter) throws XGBoostError {
|
||||
long[] handles = dMatrixs2handles(evalMatrixs);
|
||||
String[] evalInfo = new String[1];
|
||||
JNIErrorHandle.checkCall(XgboostJNI.XGBoosterEvalOneIter(handle, iter, handles, evalNames, evalInfo));
|
||||
return evalInfo[0];
|
||||
}
|
||||
|
||||
/**
|
||||
* evaluate with given customized Evaluation class
|
||||
*
|
||||
* @param evalMatrixs evaluation matrix
|
||||
* @param evalNames evaluation names
|
||||
* @param eval custom evaluator
|
||||
* @return eval information
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public String evalSet(DMatrix[] evalMatrixs, String[] evalNames, IEvaluation eval)
|
||||
throws XGBoostError {
|
||||
String evalInfo = "";
|
||||
for (int i = 0; i < evalNames.length; i++) {
|
||||
String evalName = evalNames[i];
|
||||
DMatrix evalMat = evalMatrixs[i];
|
||||
float evalResult = eval.eval(predict(evalMat), evalMat);
|
||||
String evalMetric = eval.getMetric();
|
||||
evalInfo += String.format("\t%s-%s:%f", evalName, evalMetric, evalResult);
|
||||
}
|
||||
return evalInfo;
|
||||
}
|
||||
|
||||
/**
|
||||
* base function for Predict
|
||||
*
|
||||
* @param data data
|
||||
* @param outPutMargin output margin
|
||||
* @param treeLimit limit number of trees
|
||||
* @param predLeaf prediction minimum to keep leafs
|
||||
* @return predict results
|
||||
*/
|
||||
private synchronized float[][] pred(DMatrix data, boolean outPutMargin, int treeLimit,
|
||||
boolean predLeaf) throws XGBoostError {
|
||||
int optionMask = 0;
|
||||
if (outPutMargin) {
|
||||
optionMask = 1;
|
||||
}
|
||||
if (predLeaf) {
|
||||
optionMask = 2;
|
||||
}
|
||||
float[][] rawPredicts = new float[1][];
|
||||
JNIErrorHandle.checkCall(XgboostJNI.XGBoosterPredict(handle, data.getHandle(), optionMask,
|
||||
treeLimit, rawPredicts));
|
||||
int row = (int) data.rowNum();
|
||||
int col = rawPredicts[0].length / row;
|
||||
float[][] predicts = new float[row][col];
|
||||
int r, c;
|
||||
for (int i = 0; i < rawPredicts[0].length; i++) {
|
||||
r = i / col;
|
||||
c = i % col;
|
||||
predicts[r][c] = rawPredicts[0][i];
|
||||
}
|
||||
return predicts;
|
||||
}
|
||||
|
||||
/**
|
||||
* Predict with data
|
||||
*
|
||||
* @param data dmatrix storing the input
|
||||
* @return predict result
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public float[][] predict(DMatrix data) throws XGBoostError {
|
||||
return pred(data, false, 0, false);
|
||||
}
|
||||
|
||||
/**
|
||||
* Predict with data
|
||||
*
|
||||
* @param data dmatrix storing the input
|
||||
* @param outPutMargin Whether to output the raw untransformed margin value.
|
||||
* @return predict result
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public float[][] predict(DMatrix data, boolean outPutMargin) throws XGBoostError {
|
||||
return pred(data, outPutMargin, 0, false);
|
||||
}
|
||||
|
||||
/**
|
||||
* Predict with data
|
||||
*
|
||||
* @param data dmatrix storing the input
|
||||
* @param outPutMargin Whether to output the raw untransformed margin value.
|
||||
* @param treeLimit Limit number of trees in the prediction; defaults to 0 (use all trees).
|
||||
* @return predict result
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public float[][] predict(DMatrix data, boolean outPutMargin, int treeLimit) throws XGBoostError {
|
||||
return pred(data, outPutMargin, treeLimit, false);
|
||||
}
|
||||
|
||||
/**
|
||||
* Predict with data
|
||||
*
|
||||
* @param data dmatrix storing the input
|
||||
* @param treeLimit Limit number of trees in the prediction; defaults to 0 (use all trees).
|
||||
* @param predLeaf When this option is on, the output will be a matrix of (nsample, ntrees),
|
||||
* nsample = data.numRow with each record indicating the predicted leaf index
|
||||
* of each sample in each tree.
|
||||
* Note that the leaf index of a tree is unique per tree, so you may find leaf 1
|
||||
* in both tree 1 and tree 0.
|
||||
* @return predict result
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public float[][] predict(DMatrix data, int treeLimit, boolean predLeaf) throws XGBoostError {
|
||||
return pred(data, false, treeLimit, predLeaf);
|
||||
}
|
||||
|
||||
/**
|
||||
* save model to modelPath
|
||||
*
|
||||
* @param modelPath model path
|
||||
*/
|
||||
public void saveModel(String modelPath) throws XGBoostError{
|
||||
JNIErrorHandle.checkCall(XgboostJNI.XGBoosterSaveModel(handle, modelPath));
|
||||
}
|
||||
|
||||
private void loadModel(String modelPath) {
|
||||
XgboostJNI.XGBoosterLoadModel(handle, modelPath);
|
||||
}
|
||||
|
||||
/**
|
||||
* get the dump of the model as a string array
|
||||
*
|
||||
* @param withStats Controls whether the split statistics are output.
|
||||
* @return dumped model information
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
private String[] getDumpInfo(boolean withStats) throws XGBoostError {
|
||||
int statsFlag = 0;
|
||||
if (withStats) {
|
||||
statsFlag = 1;
|
||||
}
|
||||
String[][] modelInfos = new String[1][];
|
||||
JNIErrorHandle.checkCall(XgboostJNI.XGBoosterDumpModel(handle, "", statsFlag, modelInfos));
|
||||
return modelInfos[0];
|
||||
}
|
||||
|
||||
/**
|
||||
* get the dump of the model as a string array
|
||||
*
|
||||
* @param featureMap featureMap file
|
||||
* @param withStats Controls whether the split statistics are output.
|
||||
* @return dumped model information
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
private String[] getDumpInfo(String featureMap, boolean withStats) throws XGBoostError {
|
||||
int statsFlag = 0;
|
||||
if (withStats) {
|
||||
statsFlag = 1;
|
||||
}
|
||||
String[][] modelInfos = new String[1][];
|
||||
JNIErrorHandle.checkCall(XgboostJNI.XGBoosterDumpModel(handle, featureMap, statsFlag, modelInfos));
|
||||
return modelInfos[0];
|
||||
}
|
||||
|
||||
/**
|
||||
* Dump model into a text file.
|
||||
*
|
||||
* @param modelPath file to save dumped model info
|
||||
* @param withStats bool
|
||||
* Controls whether the split statistics are output.
|
||||
* @throws FileNotFoundException file not found
|
||||
* @throws UnsupportedEncodingException unsupported feature
|
||||
* @throws IOException error with model writing
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public void dumpModel(String modelPath, boolean withStats) throws IOException, XGBoostError {
|
||||
File tf = new File(modelPath);
|
||||
FileOutputStream out = new FileOutputStream(tf);
|
||||
BufferedWriter writer = new BufferedWriter(new OutputStreamWriter(out, "UTF-8"));
|
||||
String[] modelInfos = getDumpInfo(withStats);
|
||||
|
||||
for (int i = 0; i < modelInfos.length; i++) {
|
||||
writer.write("booster [" + i + "]:\n");
|
||||
writer.write(modelInfos[i]);
|
||||
}
|
||||
|
||||
writer.close();
|
||||
out.close();
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* Dump model into a text file.
|
||||
*
|
||||
* @param modelPath file to save dumped model info
|
||||
* @param featureMap featureMap file
|
||||
* @param withStats bool
|
||||
* Controls whether the split statistics are output.
|
||||
* @throws FileNotFoundException exception
|
||||
* @throws UnsupportedEncodingException exception
|
||||
* @throws IOException exception
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public void dumpModel(String modelPath, String featureMap, boolean withStats) throws
|
||||
IOException, XGBoostError {
|
||||
File tf = new File(modelPath);
|
||||
FileOutputStream out = new FileOutputStream(tf);
|
||||
BufferedWriter writer = new BufferedWriter(new OutputStreamWriter(out, "UTF-8"));
|
||||
String[] modelInfos = getDumpInfo(featureMap, withStats);
|
||||
|
||||
for (int i = 0; i < modelInfos.length; i++) {
|
||||
writer.write("booster [" + i + "]:\n");
|
||||
writer.write(modelInfos[i]);
|
||||
}
|
||||
|
||||
writer.close();
|
||||
out.close();
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* get importance of each feature
|
||||
*
|
||||
* @return featureMap key: feature index, value: feature importance score
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public Map<String, Integer> getFeatureScore() throws XGBoostError {
|
||||
String[] modelInfos = getDumpInfo(false);
|
||||
Map<String, Integer> featureScore = new HashMap<String, Integer>();
|
||||
for (String tree : modelInfos) {
|
||||
for (String node : tree.split("\n")) {
|
||||
String[] array = node.split("\\[");
|
||||
if (array.length == 1) {
|
||||
continue;
|
||||
}
|
||||
String fid = array[1].split("\\]")[0];
|
||||
fid = fid.split("<")[0];
|
||||
if (featureScore.containsKey(fid)) {
|
||||
featureScore.put(fid, 1 + featureScore.get(fid));
|
||||
} else {
|
||||
featureScore.put(fid, 1);
|
||||
}
|
||||
}
|
||||
}
|
||||
return featureScore;
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* get importance of each feature
|
||||
*
|
||||
* @param featureMap file to save dumped model info
|
||||
* @return featureMap key: feature index, value: feature importance score
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public Map<String, Integer> getFeatureScore(String featureMap) throws XGBoostError {
|
||||
String[] modelInfos = getDumpInfo(featureMap, false);
|
||||
Map<String, Integer> featureScore = new HashMap<String, Integer>();
|
||||
for (String tree : modelInfos) {
|
||||
for (String node : tree.split("\n")) {
|
||||
String[] array = node.split("\\[");
|
||||
if (array.length == 1) {
|
||||
continue;
|
||||
}
|
||||
String fid = array[1].split("\\]")[0];
|
||||
fid = fid.split("<")[0];
|
||||
if (featureScore.containsKey(fid)) {
|
||||
featureScore.put(fid, 1 + featureScore.get(fid));
|
||||
} else {
|
||||
featureScore.put(fid, 1);
|
||||
}
|
||||
}
|
||||
}
|
||||
return featureScore;
|
||||
}
|
||||
|
||||
/**
|
||||
* transfer DMatrix array to handle array (used for native functions)
|
||||
*
|
||||
* @param dmatrixs
|
||||
* @return handle array for input dmatrixs
|
||||
*/
|
||||
private static long[] dMatrixs2handles(DMatrix[] dmatrixs) {
|
||||
long[] handles = new long[dmatrixs.length];
|
||||
for (int i = 0; i < dmatrixs.length; i++) {
|
||||
handles[i] = dmatrixs[i].getHandle();
|
||||
}
|
||||
return handles;
|
||||
}
|
||||
|
||||
@Override
|
||||
protected void finalize() throws Throwable {
|
||||
super.finalize();
|
||||
dispose();
|
||||
}
|
||||
|
||||
public synchronized void dispose() {
|
||||
if (handle != 0L) {
|
||||
XgboostJNI.XGBoosterFree(handle);
|
||||
handle = 0;
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,168 @@
|
||||
/*
|
||||
Copyright (c) 2014 by Contributors
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
*/
|
||||
package org.dmlc.xgboost4j;
|
||||
|
||||
import org.apache.commons.logging.Log;
|
||||
import org.apache.commons.logging.LogFactory;
|
||||
|
||||
import java.io.*;
|
||||
import java.lang.reflect.Field;
|
||||
|
||||
/**
|
||||
* class to load native library
|
||||
*
|
||||
* @author hzx
|
||||
*/
|
||||
class NativeLibLoader {
|
||||
private static final Log logger = LogFactory.getLog(NativeLibLoader.class);
|
||||
|
||||
private static boolean initialized = false;
|
||||
private static final String nativePath = "../lib/";
|
||||
private static final String nativeResourcePath = "/lib/";
|
||||
private static final String[] libNames = new String[]{"xgboost4j"};
|
||||
|
||||
public static synchronized void InitXgboost() throws IOException {
|
||||
if (!initialized) {
|
||||
for (String libName : libNames) {
|
||||
smartLoad(libName);
|
||||
}
|
||||
initialized = true;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Loads library from current JAR archive
|
||||
* <p/>
|
||||
* The file from JAR is copied into system temporary directory and then loaded.
|
||||
* The temporary file is deleted after exiting.
|
||||
* Method uses String as filename because the pathname is "abstract", not system-dependent.
|
||||
* <p/>
|
||||
* The restrictions of {@link File#createTempFile(java.lang.String, java.lang.String)} apply to {@code path}.
|
||||
*
|
||||
* @param path The filename inside JAR as absolute path (beginning with '/'), e.g. /package/File.ext
|
||||
* @throws IOException If temporary file creation or read/write operation fails
|
||||
* @throws IllegalArgumentException If source file (param path) does not exist
|
||||
* @throws IllegalArgumentException If the path is not absolute or if the filename is shorter than three characters
|
||||
*/
|
||||
private static void loadLibraryFromJar(String path) throws IOException {
|
||||
|
||||
if (!path.startsWith("/")) {
|
||||
throw new IllegalArgumentException("The path has to be absolute (start with '/').");
|
||||
}
|
||||
|
||||
// Obtain filename from path
|
||||
String[] parts = path.split("/");
|
||||
String filename = (parts.length > 1) ? parts[parts.length - 1] : null;
|
||||
|
||||
// Split filename to prexif and suffix (extension)
|
||||
String prefix = "";
|
||||
String suffix = null;
|
||||
if (filename != null) {
|
||||
parts = filename.split("\\.", 2);
|
||||
prefix = parts[0];
|
||||
suffix = (parts.length > 1) ? "." + parts[parts.length - 1] : null; // Thanks, davs! :-)
|
||||
}
|
||||
|
||||
// Check if the filename is okay
|
||||
if (filename == null || prefix.length() < 3) {
|
||||
throw new IllegalArgumentException("The filename has to be at least 3 characters long.");
|
||||
}
|
||||
|
||||
// Prepare temporary file
|
||||
File temp = File.createTempFile(prefix, suffix);
|
||||
temp.deleteOnExit();
|
||||
|
||||
if (!temp.exists()) {
|
||||
throw new FileNotFoundException("File " + temp.getAbsolutePath() + " does not exist.");
|
||||
}
|
||||
|
||||
// Prepare buffer for data copying
|
||||
byte[] buffer = new byte[1024];
|
||||
int readBytes;
|
||||
|
||||
// Open and check input stream
|
||||
InputStream is = NativeLibLoader.class.getResourceAsStream(path);
|
||||
if (is == null) {
|
||||
throw new FileNotFoundException("File " + path + " was not found inside JAR.");
|
||||
}
|
||||
|
||||
// Open output stream and copy data between source file in JAR and the temporary file
|
||||
OutputStream os = new FileOutputStream(temp);
|
||||
try {
|
||||
while ((readBytes = is.read(buffer)) != -1) {
|
||||
os.write(buffer, 0, readBytes);
|
||||
}
|
||||
} finally {
|
||||
// If read/write fails, close streams safely before throwing an exception
|
||||
os.close();
|
||||
is.close();
|
||||
}
|
||||
|
||||
// Finally, load the library
|
||||
System.load(temp.getAbsolutePath());
|
||||
}
|
||||
|
||||
/**
|
||||
* load native library, this method will first try to load library from java.library.path, then
|
||||
* try to load library in jar package.
|
||||
*
|
||||
* @param libName library path
|
||||
* @throws IOException exception
|
||||
*/
|
||||
private static void smartLoad(String libName) throws IOException {
|
||||
addNativeDir(nativePath);
|
||||
try {
|
||||
System.loadLibrary(libName);
|
||||
System.out.println("======load " + libName + " successfully");
|
||||
} catch (UnsatisfiedLinkError e) {
|
||||
try {
|
||||
String libraryFromJar = nativeResourcePath + System.mapLibraryName(libName);
|
||||
loadLibraryFromJar(libraryFromJar);
|
||||
} catch (IOException e1) {
|
||||
throw e1;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Add libPath to java.library.path, then native library in libPath would be load properly
|
||||
*
|
||||
* @param libPath library path
|
||||
* @throws IOException exception
|
||||
*/
|
||||
private static void addNativeDir(String libPath) throws IOException {
|
||||
try {
|
||||
Field field = ClassLoader.class.getDeclaredField("usr_paths");
|
||||
field.setAccessible(true);
|
||||
String[] paths = (String[]) field.get(null);
|
||||
for (String path : paths) {
|
||||
if (libPath.equals(path)) {
|
||||
return;
|
||||
}
|
||||
}
|
||||
String[] tmp = new String[paths.length + 1];
|
||||
System.arraycopy(paths, 0, tmp, 0, paths.length);
|
||||
tmp[paths.length] = libPath;
|
||||
field.set(null, tmp);
|
||||
} catch (IllegalAccessException e) {
|
||||
logger.error(e.getMessage());
|
||||
throw new IOException("Failed to get permissions to set library path");
|
||||
} catch (NoSuchFieldException e) {
|
||||
logger.error(e.getMessage());
|
||||
throw new IOException("Failed to get field handle to set library path");
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,336 @@
|
||||
/*
|
||||
Copyright (c) 2014 by Contributors
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
*/
|
||||
package org.dmlc.xgboost4j;
|
||||
|
||||
import org.apache.commons.logging.Log;
|
||||
import org.apache.commons.logging.LogFactory;
|
||||
|
||||
import java.util.*;
|
||||
|
||||
|
||||
/**
|
||||
* trainer for xgboost
|
||||
*
|
||||
* @author hzx
|
||||
*/
|
||||
public class XGBoost {
|
||||
private static final Log logger = LogFactory.getLog(XGBoost.class);
|
||||
|
||||
/**
|
||||
* Train a booster with given parameters.
|
||||
*
|
||||
* @param params Booster params.
|
||||
* @param dtrain Data to be trained.
|
||||
* @param round Number of boosting iterations.
|
||||
* @param watches a group of items to be evaluated during training, this allows user to watch
|
||||
* performance on the validation set.
|
||||
* @param obj customized objective (set to null if not used)
|
||||
* @param eval customized evaluation (set to null if not used)
|
||||
* @return trained booster
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public static Booster train(Map<String, Object> params, DMatrix dtrain, int round,
|
||||
Map<String, DMatrix> watches, IObjective obj,
|
||||
IEvaluation eval) throws XGBoostError {
|
||||
|
||||
//collect eval matrixs
|
||||
String[] evalNames;
|
||||
DMatrix[] evalMats;
|
||||
List<String> names = new ArrayList<String>();
|
||||
List<DMatrix> mats = new ArrayList<DMatrix>();
|
||||
|
||||
for (Map.Entry<String, DMatrix> evalEntry : watches.entrySet()) {
|
||||
names.add(evalEntry.getKey());
|
||||
mats.add(evalEntry.getValue());
|
||||
}
|
||||
|
||||
evalNames = names.toArray(new String[names.size()]);
|
||||
evalMats = mats.toArray(new DMatrix[mats.size()]);
|
||||
|
||||
//collect all data matrixs
|
||||
DMatrix[] allMats;
|
||||
if (evalMats != null && evalMats.length > 0) {
|
||||
allMats = new DMatrix[evalMats.length + 1];
|
||||
allMats[0] = dtrain;
|
||||
System.arraycopy(evalMats, 0, allMats, 1, evalMats.length);
|
||||
} else {
|
||||
allMats = new DMatrix[1];
|
||||
allMats[0] = dtrain;
|
||||
}
|
||||
|
||||
//initialize booster
|
||||
Booster booster = new JavaBoosterImpl(params, allMats);
|
||||
|
||||
//begin to train
|
||||
for (int iter = 0; iter < round; iter++) {
|
||||
if (obj != null) {
|
||||
booster.update(dtrain, obj);
|
||||
} else {
|
||||
booster.update(dtrain, iter);
|
||||
}
|
||||
|
||||
//evaluation
|
||||
if (evalMats != null && evalMats.length > 0) {
|
||||
String evalInfo;
|
||||
if (eval != null) {
|
||||
evalInfo = booster.evalSet(evalMats, evalNames, eval);
|
||||
} else {
|
||||
evalInfo = booster.evalSet(evalMats, evalNames, iter);
|
||||
}
|
||||
logger.info(evalInfo);
|
||||
}
|
||||
}
|
||||
return booster;
|
||||
}
|
||||
|
||||
/**
|
||||
* init Booster from dMatrixs
|
||||
*
|
||||
* @param params parameters
|
||||
* @param dMatrixs DMatrix array
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public static Booster initBoostingModel(
|
||||
Map<String, Object> params,
|
||||
DMatrix[] dMatrixs) throws XGBoostError {
|
||||
return new JavaBoosterImpl(params, dMatrixs);
|
||||
}
|
||||
|
||||
/**
|
||||
* load model from modelPath
|
||||
*
|
||||
* @param params parameters
|
||||
* @param modelPath booster modelPath (model generated by booster.saveModel)
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public static Booster loadBoostModel(Map<String, Object> params, String modelPath)
|
||||
throws XGBoostError {
|
||||
return new JavaBoosterImpl(params, modelPath);
|
||||
}
|
||||
|
||||
/**
|
||||
* Cross-validation with given paramaters.
|
||||
*
|
||||
* @param params Booster params.
|
||||
* @param data Data to be trained.
|
||||
* @param round Number of boosting iterations.
|
||||
* @param nfold Number of folds in CV.
|
||||
* @param metrics Evaluation metrics to be watched in CV.
|
||||
* @param obj customized objective (set to null if not used)
|
||||
* @param eval customized evaluation (set to null if not used)
|
||||
* @return evaluation history
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public static String[] crossValiation(
|
||||
Map<String, Object> params,
|
||||
DMatrix data,
|
||||
int round,
|
||||
int nfold,
|
||||
String[] metrics,
|
||||
IObjective obj,
|
||||
IEvaluation eval) throws XGBoostError {
|
||||
CVPack[] cvPacks = makeNFold(data, nfold, params, metrics);
|
||||
String[] evalHist = new String[round];
|
||||
String[] results = new String[cvPacks.length];
|
||||
for (int i = 0; i < round; i++) {
|
||||
for (CVPack cvPack : cvPacks) {
|
||||
if (obj != null) {
|
||||
cvPack.update(obj);
|
||||
} else {
|
||||
cvPack.update(i);
|
||||
}
|
||||
}
|
||||
|
||||
for (int j = 0; j < cvPacks.length; j++) {
|
||||
if (eval != null) {
|
||||
results[j] = cvPacks[j].eval(eval);
|
||||
} else {
|
||||
results[j] = cvPacks[j].eval(i);
|
||||
}
|
||||
}
|
||||
|
||||
evalHist[i] = aggCVResults(results);
|
||||
logger.info(evalHist[i]);
|
||||
}
|
||||
return evalHist;
|
||||
}
|
||||
|
||||
/**
|
||||
* make an n-fold array of CVPack from random indices
|
||||
*
|
||||
* @param data original data
|
||||
* @param nfold num of folds
|
||||
* @param params booster parameters
|
||||
* @param evalMetrics Evaluation metrics
|
||||
* @return CV package array
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
private static CVPack[] makeNFold(DMatrix data, int nfold, Map<String, Object> params,
|
||||
String[] evalMetrics) throws XGBoostError {
|
||||
List<Integer> samples = genRandPermutationNums(0, (int) data.rowNum());
|
||||
int step = samples.size() / nfold;
|
||||
int[] testSlice = new int[step];
|
||||
int[] trainSlice = new int[samples.size() - step];
|
||||
int testid, trainid;
|
||||
CVPack[] cvPacks = new CVPack[nfold];
|
||||
for (int i = 0; i < nfold; i++) {
|
||||
testid = 0;
|
||||
trainid = 0;
|
||||
for (int j = 0; j < samples.size(); j++) {
|
||||
if (j > (i * step) && j < (i * step + step) && testid < step) {
|
||||
testSlice[testid] = samples.get(j);
|
||||
testid++;
|
||||
} else {
|
||||
if (trainid < samples.size() - step) {
|
||||
trainSlice[trainid] = samples.get(j);
|
||||
trainid++;
|
||||
} else {
|
||||
testSlice[testid] = samples.get(j);
|
||||
testid++;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
DMatrix dtrain = data.slice(trainSlice);
|
||||
DMatrix dtest = data.slice(testSlice);
|
||||
CVPack cvPack = new CVPack(dtrain, dtest, params);
|
||||
//set eval types
|
||||
if (evalMetrics != null) {
|
||||
for (String type : evalMetrics) {
|
||||
cvPack.booster.setParam("eval_metric", type);
|
||||
}
|
||||
}
|
||||
cvPacks[i] = cvPack;
|
||||
}
|
||||
|
||||
return cvPacks;
|
||||
}
|
||||
|
||||
private static List<Integer> genRandPermutationNums(int start, int end) {
|
||||
List<Integer> samples = new ArrayList<Integer>();
|
||||
for (int i = start; i < end; i++) {
|
||||
samples.add(i);
|
||||
}
|
||||
Collections.shuffle(samples);
|
||||
return samples;
|
||||
}
|
||||
|
||||
/**
|
||||
* Aggregate cross-validation results.
|
||||
*
|
||||
* @param results eval info from each data sample
|
||||
* @return cross-validation eval info
|
||||
*/
|
||||
private static String aggCVResults(String[] results) {
|
||||
Map<String, List<Float>> cvMap = new HashMap<String, List<Float>>();
|
||||
String aggResult = results[0].split("\t")[0];
|
||||
for (String result : results) {
|
||||
String[] items = result.split("\t");
|
||||
for (int i = 1; i < items.length; i++) {
|
||||
String[] tup = items[i].split(":");
|
||||
String key = tup[0];
|
||||
Float value = Float.valueOf(tup[1]);
|
||||
if (!cvMap.containsKey(key)) {
|
||||
cvMap.put(key, new ArrayList<Float>());
|
||||
}
|
||||
cvMap.get(key).add(value);
|
||||
}
|
||||
}
|
||||
|
||||
for (String key : cvMap.keySet()) {
|
||||
float value = 0f;
|
||||
for (Float tvalue : cvMap.get(key)) {
|
||||
value += tvalue;
|
||||
}
|
||||
value /= cvMap.get(key).size();
|
||||
aggResult += String.format("\tcv-%s:%f", key, value);
|
||||
}
|
||||
|
||||
return aggResult;
|
||||
}
|
||||
|
||||
/**
|
||||
* cross validation package for xgb
|
||||
*
|
||||
* @author hzx
|
||||
*/
|
||||
private static class CVPack {
|
||||
DMatrix dtrain;
|
||||
DMatrix dtest;
|
||||
DMatrix[] dmats;
|
||||
String[] names;
|
||||
Booster booster;
|
||||
|
||||
/**
|
||||
* create an cross validation package
|
||||
*
|
||||
* @param dtrain train data
|
||||
* @param dtest test data
|
||||
* @param params parameters
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public CVPack(DMatrix dtrain, DMatrix dtest, Map<String, Object> params)
|
||||
throws XGBoostError {
|
||||
dmats = new DMatrix[]{dtrain, dtest};
|
||||
booster = XGBoost.initBoostingModel(params, dmats);
|
||||
names = new String[]{"train", "test"};
|
||||
this.dtrain = dtrain;
|
||||
this.dtest = dtest;
|
||||
}
|
||||
|
||||
/**
|
||||
* update one iteration
|
||||
*
|
||||
* @param iter iteration num
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public void update(int iter) throws XGBoostError {
|
||||
booster.update(dtrain, iter);
|
||||
}
|
||||
|
||||
/**
|
||||
* update one iteration
|
||||
*
|
||||
* @param obj customized objective
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public void update(IObjective obj) throws XGBoostError {
|
||||
booster.update(dtrain, obj);
|
||||
}
|
||||
|
||||
/**
|
||||
* evaluation
|
||||
*
|
||||
* @param iter iteration num
|
||||
* @return evaluation
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public String eval(int iter) throws XGBoostError {
|
||||
return booster.evalSet(dmats, names, iter);
|
||||
}
|
||||
|
||||
/**
|
||||
* evaluation
|
||||
*
|
||||
* @param eval customized eval
|
||||
* @return evaluation
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
public String eval(IEvaluation eval) throws XGBoostError {
|
||||
return booster.evalSet(dmats, names, eval);
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -13,14 +13,15 @@
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
*/
|
||||
package org.dmlc.xgboost4j.util;
|
||||
package org.dmlc.xgboost4j;
|
||||
|
||||
/**
|
||||
* custom error class for xgboost
|
||||
*
|
||||
* @author hzx
|
||||
*/
|
||||
public class XGBoostError extends Exception{
|
||||
public XGBoostError(String message) {
|
||||
super(message);
|
||||
}
|
||||
public class XGBoostError extends Exception {
|
||||
public XGBoostError(String message) {
|
||||
super(message);
|
||||
}
|
||||
}
|
||||
@ -13,38 +13,71 @@
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
*/
|
||||
package org.dmlc.xgboost4j.wrapper;
|
||||
package org.dmlc.xgboost4j;
|
||||
|
||||
/**
|
||||
* xgboost jni wrapper functions for xgboost_wrapper.h
|
||||
* change 2015-7-6: *use a long[] (length=1) as container of handle to get the output DMatrix or Booster
|
||||
*
|
||||
* @author hzx
|
||||
*/
|
||||
public class XgboostJNI {
|
||||
class XgboostJNI {
|
||||
public final static native String XGBGetLastError();
|
||||
|
||||
public final static native int XGDMatrixCreateFromFile(String fname, int silent, long[] out);
|
||||
public final static native int XGDMatrixCreateFromCSR(long[] indptr, int[] indices, float[] data, long[] out);
|
||||
public final static native int XGDMatrixCreateFromCSC(long[] colptr, int[] indices, float[] data, long[] out);
|
||||
public final static native int XGDMatrixCreateFromMat(float[] data, int nrow, int ncol, float missing, long[] out);
|
||||
|
||||
public final static native int XGDMatrixCreateFromCSR(long[] indptr, int[] indices, float[] data,
|
||||
long[] out);
|
||||
|
||||
public final static native int XGDMatrixCreateFromCSC(long[] colptr, int[] indices, float[] data,
|
||||
long[] out);
|
||||
|
||||
public final static native int XGDMatrixCreateFromMat(float[] data, int nrow, int ncol,
|
||||
float missing, long[] out);
|
||||
|
||||
public final static native int XGDMatrixSliceDMatrix(long handle, int[] idxset, long[] out);
|
||||
|
||||
public final static native int XGDMatrixFree(long handle);
|
||||
|
||||
public final static native int XGDMatrixSaveBinary(long handle, String fname, int silent);
|
||||
|
||||
public final static native int XGDMatrixSetFloatInfo(long handle, String field, float[] array);
|
||||
|
||||
public final static native int XGDMatrixSetUIntInfo(long handle, String field, int[] array);
|
||||
|
||||
public final static native int XGDMatrixSetGroup(long handle, int[] group);
|
||||
|
||||
public final static native int XGDMatrixGetFloatInfo(long handle, String field, float[][] info);
|
||||
|
||||
public final static native int XGDMatrixGetUIntInfo(long handle, String filed, int[][] info);
|
||||
|
||||
public final static native int XGDMatrixNumRow(long handle, long[] row);
|
||||
|
||||
public final static native int XGBoosterCreate(long[] handles, long[] out);
|
||||
|
||||
public final static native int XGBoosterFree(long handle);
|
||||
|
||||
public final static native int XGBoosterSetParam(long handle, String name, String value);
|
||||
|
||||
public final static native int XGBoosterUpdateOneIter(long handle, int iter, long dtrain);
|
||||
public final static native int XGBoosterBoostOneIter(long handle, long dtrain, float[] grad, float[] hess);
|
||||
public final static native int XGBoosterEvalOneIter(long handle, int iter, long[] dmats, String[] evnames, String[] eval_info);
|
||||
public final static native int XGBoosterPredict(long handle, long dmat, int option_mask, int ntree_limit, float[][] predicts);
|
||||
|
||||
public final static native int XGBoosterBoostOneIter(long handle, long dtrain, float[] grad,
|
||||
float[] hess);
|
||||
|
||||
public final static native int XGBoosterEvalOneIter(long handle, int iter, long[] dmats,
|
||||
String[] evnames, String[] eval_info);
|
||||
|
||||
public final static native int XGBoosterPredict(long handle, long dmat, int option_mask,
|
||||
int ntree_limit, float[][] predicts);
|
||||
|
||||
public final static native int XGBoosterLoadModel(long handle, String fname);
|
||||
|
||||
public final static native int XGBoosterSaveModel(long handle, String fname);
|
||||
|
||||
public final static native int XGBoosterLoadModelFromBuffer(long handle, long buf, long len);
|
||||
|
||||
public final static native int XGBoosterGetModelRaw(long handle, String[] out_string);
|
||||
public final static native int XGBoosterDumpModel(long handle, String fmap, int with_stats, String[][] out_strings);
|
||||
|
||||
public final static native int XGBoosterDumpModel(long handle, String fmap, int with_stats,
|
||||
String[][] out_strings);
|
||||
}
|
||||
@ -0,0 +1,172 @@
|
||||
package org.dmlc.xgboost4j.scala
|
||||
|
||||
import java.io.IOException
|
||||
|
||||
import scala.collection.mutable
|
||||
|
||||
import org.dmlc.xgboost4j.{IEvaluation, IObjective, XGBoostError}
|
||||
|
||||
trait Booster {
|
||||
|
||||
|
||||
/**
|
||||
* set parameter
|
||||
*
|
||||
* @param key param name
|
||||
* @param value param value
|
||||
*/
|
||||
@throws(classOf[XGBoostError])
|
||||
def setParam(key: String, value: String)
|
||||
|
||||
/**
|
||||
* set parameters
|
||||
*
|
||||
* @param params parameters key-value map
|
||||
*/
|
||||
@throws(classOf[XGBoostError])
|
||||
def setParams(params: Map[String, AnyRef])
|
||||
|
||||
/**
|
||||
* Update (one iteration)
|
||||
*
|
||||
* @param dtrain training data
|
||||
* @param iter current iteration number
|
||||
*/
|
||||
@throws(classOf[XGBoostError])
|
||||
def update(dtrain: DMatrix, iter: Int)
|
||||
|
||||
/**
|
||||
* update with customize obj func
|
||||
*
|
||||
* @param dtrain training data
|
||||
* @param obj customized objective class
|
||||
*/
|
||||
@throws(classOf[XGBoostError])
|
||||
def update(dtrain: DMatrix, obj: IObjective)
|
||||
|
||||
/**
|
||||
* update with give grad and hess
|
||||
*
|
||||
* @param dtrain training data
|
||||
* @param grad first order of gradient
|
||||
* @param hess seconde order of gradient
|
||||
*/
|
||||
@throws(classOf[XGBoostError])
|
||||
def boost(dtrain: DMatrix, grad: Array[Float], hess: Array[Float])
|
||||
|
||||
/**
|
||||
* evaluate with given dmatrixs.
|
||||
*
|
||||
* @param evalMatrixs dmatrixs for evaluation
|
||||
* @param evalNames name for eval dmatrixs, used for check results
|
||||
* @param iter current eval iteration
|
||||
* @return eval information
|
||||
*/
|
||||
@throws(classOf[XGBoostError])
|
||||
def evalSet(evalMatrixs: Array[DMatrix], evalNames: Array[String], iter: Int): String
|
||||
|
||||
/**
|
||||
* evaluate with given customized Evaluation class
|
||||
*
|
||||
* @param evalMatrixs evaluation matrix
|
||||
* @param evalNames evaluation names
|
||||
* @param eval custom evaluator
|
||||
* @return eval information
|
||||
*/
|
||||
@throws(classOf[XGBoostError])
|
||||
def evalSet(evalMatrixs: Array[DMatrix], evalNames: Array[String], eval: IEvaluation): String
|
||||
|
||||
/**
|
||||
* Predict with data
|
||||
*
|
||||
* @param data dmatrix storing the input
|
||||
* @return predict result
|
||||
*/
|
||||
@throws(classOf[XGBoostError])
|
||||
def predict(data: DMatrix): Array[Array[Float]]
|
||||
|
||||
/**
|
||||
* Predict with data
|
||||
*
|
||||
* @param data dmatrix storing the input
|
||||
* @param outPutMargin Whether to output the raw untransformed margin value.
|
||||
* @return predict result
|
||||
*/
|
||||
@throws(classOf[XGBoostError])
|
||||
def predict(data: DMatrix, outPutMargin: Boolean): Array[Array[Float]]
|
||||
|
||||
/**
|
||||
* Predict with data
|
||||
*
|
||||
* @param data dmatrix storing the input
|
||||
* @param outPutMargin Whether to output the raw untransformed margin value.
|
||||
* @param treeLimit Limit number of trees in the prediction; defaults to 0 (use all trees).
|
||||
* @return predict result
|
||||
*/
|
||||
@throws(classOf[XGBoostError])
|
||||
def predict(data: DMatrix, outPutMargin: Boolean, treeLimit: Int): Array[Array[Float]]
|
||||
|
||||
/**
|
||||
* Predict with data
|
||||
*
|
||||
* @param data dmatrix storing the input
|
||||
* @param treeLimit Limit number of trees in the prediction; defaults to 0 (use all trees).
|
||||
* @param predLeaf When this option is on, the output will be a matrix of (nsample, ntrees), nsample = data.numRow
|
||||
with each record indicating the predicted leaf index of each sample in each tree.
|
||||
Note that the leaf index of a tree is unique per tree, so you may find leaf 1
|
||||
in both tree 1 and tree 0.
|
||||
* @return predict result
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
@throws(classOf[XGBoostError])
|
||||
def predict(data: DMatrix, treeLimit: Int, predLeaf: Boolean): Array[Array[Float]]
|
||||
|
||||
/**
|
||||
* save model to modelPath
|
||||
*
|
||||
* @param modelPath model path
|
||||
*/
|
||||
@throws(classOf[XGBoostError])
|
||||
def saveModel(modelPath: String)
|
||||
|
||||
/**
|
||||
* Dump model into a text file.
|
||||
*
|
||||
* @param modelPath file to save dumped model info
|
||||
* @param withStats bool Controls whether the split statistics are output.
|
||||
*/
|
||||
@throws(classOf[IOException])
|
||||
@throws(classOf[XGBoostError])
|
||||
def dumpModel(modelPath: String, withStats: Boolean)
|
||||
|
||||
/**
|
||||
* Dump model into a text file.
|
||||
*
|
||||
* @param modelPath file to save dumped model info
|
||||
* @param featureMap featureMap file
|
||||
* @param withStats bool
|
||||
* Controls whether the split statistics are output.
|
||||
*/
|
||||
@throws(classOf[IOException])
|
||||
@throws(classOf[XGBoostError])
|
||||
def dumpModel(modelPath: String, featureMap: String, withStats: Boolean)
|
||||
|
||||
/**
|
||||
* get importance of each feature
|
||||
*
|
||||
* @return featureMap key: feature index, value: feature importance score
|
||||
*/
|
||||
@throws(classOf[XGBoostError])
|
||||
def getFeatureScore: mutable.Map[String, Integer]
|
||||
|
||||
/**
|
||||
* get importance of each feature
|
||||
*
|
||||
* @param featureMap file to save dumped model info
|
||||
* @return featureMap key: feature index, value: feature importance score
|
||||
*/
|
||||
@throws(classOf[XGBoostError])
|
||||
def getFeatureScore(featureMap: String): mutable.Map[String, Integer]
|
||||
|
||||
def dispose
|
||||
}
|
||||
@ -0,0 +1,161 @@
|
||||
package org.dmlc.xgboost4j.scala
|
||||
|
||||
import org.dmlc.xgboost4j.{DMatrix => JDMatrix, XGBoostError}
|
||||
|
||||
class DMatrix private(private[scala] val jDMatrix: JDMatrix) {
|
||||
|
||||
/**
|
||||
* init DMatrix from file (svmlight format)
|
||||
*
|
||||
* @param dataPath path of data file
|
||||
* @throws XGBoostError native error
|
||||
*/
|
||||
def this(dataPath: String) {
|
||||
this(new JDMatrix(dataPath))
|
||||
}
|
||||
|
||||
/**
|
||||
* create DMatrix from sparse matrix
|
||||
*
|
||||
* @param headers index to headers (rowHeaders for CSR or colHeaders for CSC)
|
||||
* @param indices Indices (colIndexs for CSR or rowIndexs for CSC)
|
||||
* @param data non zero values (sequence by row for CSR or by col for CSC)
|
||||
* @param st sparse matrix type (CSR or CSC)
|
||||
*/
|
||||
@throws(classOf[XGBoostError])
|
||||
def this(headers: Array[Long], indices: Array[Int], data: Array[Float], st: JDMatrix.SparseType) {
|
||||
this(new JDMatrix(headers, indices, data, st))
|
||||
}
|
||||
|
||||
/**
|
||||
* create DMatrix from dense matrix
|
||||
*
|
||||
* @param data data values
|
||||
* @param nrow number of rows
|
||||
* @param ncol number of columns
|
||||
*/
|
||||
@throws(classOf[XGBoostError])
|
||||
def this(data: Array[Float], nrow: Int, ncol: Int) {
|
||||
this(new JDMatrix(data, nrow, ncol))
|
||||
}
|
||||
|
||||
/**
|
||||
* set label of dmatrix
|
||||
*
|
||||
* @param labels labels
|
||||
*/
|
||||
@throws(classOf[XGBoostError])
|
||||
def setLabel(labels: Array[Float]): Unit = {
|
||||
jDMatrix.setLabel(labels)
|
||||
}
|
||||
|
||||
/**
|
||||
* set weight of each instance
|
||||
*
|
||||
* @param weights weights
|
||||
*/
|
||||
@throws(classOf[XGBoostError])
|
||||
def setWeight(weights: Array[Float]): Unit = {
|
||||
jDMatrix.setWeight(weights)
|
||||
}
|
||||
|
||||
/**
|
||||
* if specified, xgboost will start from this init margin
|
||||
* can be used to specify initial prediction to boost from
|
||||
*
|
||||
* @param baseMargin base margin
|
||||
*/
|
||||
@throws(classOf[XGBoostError])
|
||||
def setBaseMargin(baseMargin: Array[Float]): Unit = {
|
||||
jDMatrix.setBaseMargin(baseMargin)
|
||||
}
|
||||
|
||||
/**
|
||||
* if specified, xgboost will start from this init margin
|
||||
* can be used to specify initial prediction to boost from
|
||||
*
|
||||
* @param baseMargin base margin
|
||||
*/
|
||||
@throws(classOf[XGBoostError])
|
||||
def setBaseMargin(baseMargin: Array[Array[Float]]): Unit = {
|
||||
jDMatrix.setBaseMargin(baseMargin)
|
||||
}
|
||||
|
||||
/**
|
||||
* Set group sizes of DMatrix (used for ranking)
|
||||
*
|
||||
* @param group group size as array
|
||||
*/
|
||||
@throws(classOf[XGBoostError])
|
||||
def setGroup(group: Array[Int]): Unit = {
|
||||
jDMatrix.setGroup(group)
|
||||
}
|
||||
|
||||
/**
|
||||
* get label values
|
||||
*
|
||||
* @return label
|
||||
*/
|
||||
@throws(classOf[XGBoostError])
|
||||
def getLabel: Array[Float] = {
|
||||
jDMatrix.getLabel
|
||||
}
|
||||
|
||||
/**
|
||||
* get weight of the DMatrix
|
||||
*
|
||||
* @return weights
|
||||
*/
|
||||
@throws(classOf[XGBoostError])
|
||||
def getWeight: Array[Float] = {
|
||||
jDMatrix.getWeight
|
||||
}
|
||||
|
||||
/**
|
||||
* get base margin of the DMatrix
|
||||
*
|
||||
* @return base margin
|
||||
*/
|
||||
@throws(classOf[XGBoostError])
|
||||
def getBaseMargin: Array[Float] = {
|
||||
jDMatrix.getBaseMargin
|
||||
}
|
||||
|
||||
/**
|
||||
* Slice the DMatrix and return a new DMatrix that only contains `rowIndex`.
|
||||
*
|
||||
* @param rowIndex row index
|
||||
* @return sliced new DMatrix
|
||||
*/
|
||||
@throws(classOf[XGBoostError])
|
||||
def slice(rowIndex: Array[Int]): DMatrix = {
|
||||
new DMatrix(jDMatrix.slice(rowIndex))
|
||||
}
|
||||
|
||||
/**
|
||||
* get the row number of DMatrix
|
||||
*
|
||||
* @return number of rows
|
||||
*/
|
||||
@throws(classOf[XGBoostError])
|
||||
def rowNum: Long = {
|
||||
jDMatrix.rowNum
|
||||
}
|
||||
|
||||
/**
|
||||
* save DMatrix to filePath
|
||||
*
|
||||
* @param filePath file path
|
||||
*/
|
||||
def saveBinary(filePath: String): Unit = {
|
||||
jDMatrix.saveBinary(filePath)
|
||||
}
|
||||
|
||||
def getHandle: Long = {
|
||||
jDMatrix.getHandle
|
||||
}
|
||||
|
||||
def delete(): Unit = {
|
||||
jDMatrix.dispose()
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,82 @@
|
||||
package org.dmlc.xgboost4j.scala
|
||||
|
||||
import scala.collection.JavaConverters._
|
||||
import scala.collection.mutable
|
||||
|
||||
import org.dmlc.xgboost4j.{Booster => JBooster, IEvaluation, IObjective}
|
||||
|
||||
private[scala] class ScalaBoosterImpl private[xgboost4j](booster: JBooster) extends Booster {
|
||||
|
||||
override def setParam(key: String, value: String): Unit = {
|
||||
booster.setParam(key, value)
|
||||
}
|
||||
|
||||
override def update(dtrain: DMatrix, iter: Int): Unit = {
|
||||
booster.update(dtrain.jDMatrix, iter)
|
||||
}
|
||||
|
||||
override def update(dtrain: DMatrix, obj: IObjective): Unit = {
|
||||
booster.update(dtrain.jDMatrix, obj)
|
||||
}
|
||||
|
||||
override def dumpModel(modelPath: String, withStats: Boolean): Unit = {
|
||||
booster.dumpModel(modelPath, withStats)
|
||||
}
|
||||
|
||||
override def dumpModel(modelPath: String, featureMap: String, withStats: Boolean): Unit = {
|
||||
booster.dumpModel(modelPath, featureMap, withStats)
|
||||
}
|
||||
|
||||
override def setParams(params: Map[String, AnyRef]): Unit = {
|
||||
booster.setParams(params.asJava)
|
||||
}
|
||||
|
||||
override def evalSet(evalMatrixs: Array[DMatrix], evalNames: Array[String], iter: Int): String = {
|
||||
booster.evalSet(evalMatrixs.map(_.jDMatrix), evalNames, iter)
|
||||
}
|
||||
|
||||
override def evalSet(evalMatrixs: Array[DMatrix], evalNames: Array[String], eval: IEvaluation): String = {
|
||||
booster.evalSet(evalMatrixs.map(_.jDMatrix), evalNames, eval)
|
||||
}
|
||||
|
||||
override def dispose: Unit = {
|
||||
booster.dispose()
|
||||
}
|
||||
|
||||
override def predict(data: DMatrix): Array[Array[Float]] = {
|
||||
booster.predict(data.jDMatrix)
|
||||
}
|
||||
|
||||
override def predict(data: DMatrix, outPutMargin: Boolean): Array[Array[Float]] = {
|
||||
booster.predict(data.jDMatrix, outPutMargin)
|
||||
}
|
||||
|
||||
override def predict(data: DMatrix, outPutMargin: Boolean, treeLimit: Int): Array[Array[Float]] = {
|
||||
booster.predict(data.jDMatrix, outPutMargin, treeLimit)
|
||||
}
|
||||
|
||||
override def predict(data: DMatrix, treeLimit: Int, predLeaf: Boolean): Array[Array[Float]] = {
|
||||
booster.predict(data.jDMatrix, treeLimit, predLeaf)
|
||||
}
|
||||
|
||||
override def boost(dtrain: DMatrix, grad: Array[Float], hess: Array[Float]): Unit = {
|
||||
booster.boost(dtrain.jDMatrix, grad, hess)
|
||||
}
|
||||
|
||||
override def getFeatureScore: mutable.Map[String, Integer] = {
|
||||
booster.getFeatureScore.asScala
|
||||
}
|
||||
|
||||
override def getFeatureScore(featureMap: String): mutable.Map[String, Integer] = {
|
||||
booster.getFeatureScore(featureMap).asScala
|
||||
}
|
||||
|
||||
override def saveModel(modelPath: String): Unit = {
|
||||
booster.saveModel(modelPath)
|
||||
}
|
||||
|
||||
override def finalize(): Unit = {
|
||||
super.finalize()
|
||||
dispose
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,36 @@
|
||||
package org.dmlc.xgboost4j.scala
|
||||
|
||||
import _root_.scala.collection.JavaConverters._
|
||||
|
||||
import org.dmlc.xgboost4j
|
||||
import org.dmlc.xgboost4j.{XGBoost => JXGBoost, IEvaluation, IObjective}
|
||||
|
||||
object XGBoost {
|
||||
|
||||
def train(params: Map[String, AnyRef], dtrain: xgboost4j.DMatrix, round: Int,
|
||||
watches: Map[String, xgboost4j.DMatrix], obj: IObjective, eval: IEvaluation): Booster = {
|
||||
val xgboostInJava = JXGBoost.train(params.asJava, dtrain, round, watches.asJava, obj, eval)
|
||||
new ScalaBoosterImpl(xgboostInJava)
|
||||
}
|
||||
|
||||
def crossValiation(params: Map[String, AnyRef],
|
||||
data: DMatrix,
|
||||
round: Int,
|
||||
nfold: Int,
|
||||
metrics: Array[String],
|
||||
obj: IObjective,
|
||||
eval: IEvaluation): Array[String] = {
|
||||
JXGBoost.crossValiation(params.asJava, data.jDMatrix, round, nfold, metrics, obj,
|
||||
eval)
|
||||
}
|
||||
|
||||
def initBoostModel(params: Map[String, AnyRef], dMatrixs: Array[DMatrix]): Booster = {
|
||||
val xgboostInJava = JXGBoost.initBoostingModel(params.asJava, dMatrixs.map(_.jDMatrix))
|
||||
new ScalaBoosterImpl(xgboostInJava)
|
||||
}
|
||||
|
||||
def loadBoostModel(params: Map[String, AnyRef], modelPath: String): Booster = {
|
||||
val xgboostInJava = JXGBoost.loadBoostModel(params.asJava, modelPath)
|
||||
new ScalaBoosterImpl(xgboostInJava)
|
||||
}
|
||||
}
|
||||
@ -13,7 +13,7 @@
|
||||
*/
|
||||
|
||||
#include "xgboost/c_api.h"
|
||||
#include "xgboost4j_wrapper.h"
|
||||
#include "xgboost4j.h"
|
||||
#include <cstring>
|
||||
|
||||
//helper functions
|
||||
@ -24,7 +24,7 @@ void setHandle(JNIEnv *jenv, jlongArray jhandle, void* handle) {
|
||||
jenv->SetLongArrayRegion(jhandle, 0, 1, (const jlong*) out);
|
||||
}
|
||||
|
||||
JNIEXPORT jstring JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBGetLastError
|
||||
JNIEXPORT jstring JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGBGetLastError
|
||||
(JNIEnv *jenv, jclass jcls) {
|
||||
jstring jresult = 0 ;
|
||||
const char* result = XGBGetLastError();
|
||||
@ -32,7 +32,7 @@ JNIEXPORT jstring JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBGetLastE
|
||||
return jresult;
|
||||
}
|
||||
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixCreateFromFile
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGDMatrixCreateFromFile
|
||||
(JNIEnv *jenv, jclass jcls, jstring jfname, jint jsilent, jlongArray jout) {
|
||||
DMatrixHandle result;
|
||||
const char* fname = jenv->GetStringUTFChars(jfname, 0);
|
||||
@ -43,11 +43,11 @@ JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixCreat
|
||||
}
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGDMatrixCreateFromCSR
|
||||
* Signature: ([J[J[F)J
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixCreateFromCSR
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGDMatrixCreateFromCSR
|
||||
(JNIEnv *jenv, jclass jcls, jlongArray jindptr, jintArray jindices, jfloatArray jdata, jlongArray jout) {
|
||||
DMatrixHandle result;
|
||||
jlong* indptr = jenv->GetLongArrayElements(jindptr, 0);
|
||||
@ -65,11 +65,11 @@ JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixCreat
|
||||
}
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGDMatrixCreateFromCSC
|
||||
* Signature: ([J[J[F)J
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixCreateFromCSC
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGDMatrixCreateFromCSC
|
||||
(JNIEnv *jenv, jclass jcls, jlongArray jindptr, jintArray jindices, jfloatArray jdata, jlongArray jout) {
|
||||
DMatrixHandle result;
|
||||
jlong* indptr = jenv->GetLongArrayElements(jindptr, NULL);
|
||||
@ -89,11 +89,11 @@ JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixCreat
|
||||
}
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGDMatrixCreateFromMat
|
||||
* Signature: ([FIIF)J
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixCreateFromMat
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGDMatrixCreateFromMat
|
||||
(JNIEnv *jenv, jclass jcls, jfloatArray jdata, jint jnrow, jint jncol, jfloat jmiss, jlongArray jout) {
|
||||
DMatrixHandle result;
|
||||
jfloat* data = jenv->GetFloatArrayElements(jdata, 0);
|
||||
@ -107,11 +107,11 @@ JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixCreat
|
||||
}
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGDMatrixSliceDMatrix
|
||||
* Signature: (J[I)J
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixSliceDMatrix
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGDMatrixSliceDMatrix
|
||||
(JNIEnv *jenv, jclass jcls, jlong jhandle, jintArray jindexset, jlongArray jout) {
|
||||
DMatrixHandle result;
|
||||
DMatrixHandle handle = (DMatrixHandle) jhandle;
|
||||
@ -128,11 +128,11 @@ JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixSlice
|
||||
}
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGDMatrixFree
|
||||
* Signature: (J)V
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixFree
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGDMatrixFree
|
||||
(JNIEnv *jenv, jclass jcls, jlong jhandle) {
|
||||
DMatrixHandle handle = (DMatrixHandle) jhandle;
|
||||
int ret = XGDMatrixFree(handle);
|
||||
@ -140,11 +140,11 @@ JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixFree
|
||||
}
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGDMatrixSaveBinary
|
||||
* Signature: (JLjava/lang/String;I)V
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixSaveBinary
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGDMatrixSaveBinary
|
||||
(JNIEnv *jenv, jclass jcls, jlong jhandle, jstring jfname, jint jsilent) {
|
||||
DMatrixHandle handle = (DMatrixHandle) jhandle;
|
||||
const char* fname = jenv->GetStringUTFChars(jfname, 0);
|
||||
@ -154,11 +154,11 @@ JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixSaveB
|
||||
}
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGDMatrixSetFloatInfo
|
||||
* Signature: (JLjava/lang/String;[F)V
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixSetFloatInfo
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGDMatrixSetFloatInfo
|
||||
(JNIEnv *jenv, jclass jcls, jlong jhandle, jstring jfield, jfloatArray jarray) {
|
||||
DMatrixHandle handle = (DMatrixHandle) jhandle;
|
||||
const char* field = jenv->GetStringUTFChars(jfield, 0);
|
||||
@ -173,11 +173,11 @@ JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixSetFl
|
||||
}
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGDMatrixSetUIntInfo
|
||||
* Signature: (JLjava/lang/String;[I)V
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixSetUIntInfo
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGDMatrixSetUIntInfo
|
||||
(JNIEnv *jenv, jclass jcls, jlong jhandle, jstring jfield, jintArray jarray) {
|
||||
DMatrixHandle handle = (DMatrixHandle) jhandle;
|
||||
const char* field = jenv->GetStringUTFChars(jfield, 0);
|
||||
@ -192,11 +192,11 @@ JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixSetUI
|
||||
}
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGDMatrixSetGroup
|
||||
* Signature: (J[I)V
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixSetGroup
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGDMatrixSetGroup
|
||||
(JNIEnv * jenv, jclass jcls, jlong jhandle, jintArray jarray) {
|
||||
DMatrixHandle handle = (DMatrixHandle) jhandle;
|
||||
jint* array = jenv->GetIntArrayElements(jarray, NULL);
|
||||
@ -208,11 +208,11 @@ JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixSetGr
|
||||
}
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGDMatrixGetFloatInfo
|
||||
* Signature: (JLjava/lang/String;)[F
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixGetFloatInfo
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGDMatrixGetFloatInfo
|
||||
(JNIEnv *jenv, jclass jcls, jlong jhandle, jstring jfield, jobjectArray jout) {
|
||||
DMatrixHandle handle = (DMatrixHandle) jhandle;
|
||||
const char* field = jenv->GetStringUTFChars(jfield, 0);
|
||||
@ -230,11 +230,11 @@ JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixGetFl
|
||||
}
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGDMatrixGetUIntInfo
|
||||
* Signature: (JLjava/lang/String;)[I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixGetUIntInfo
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGDMatrixGetUIntInfo
|
||||
(JNIEnv *jenv, jclass jcls, jlong jhandle, jstring jfield, jobjectArray jout) {
|
||||
DMatrixHandle handle = (DMatrixHandle) jhandle;
|
||||
const char* field = jenv->GetStringUTFChars(jfield, 0);
|
||||
@ -251,11 +251,11 @@ JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixGetUI
|
||||
}
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGDMatrixNumRow
|
||||
* Signature: (J)J
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixNumRow
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGDMatrixNumRow
|
||||
(JNIEnv *jenv, jclass jcls, jlong jhandle, jlongArray jout) {
|
||||
DMatrixHandle handle = (DMatrixHandle) jhandle;
|
||||
bst_ulong result[1];
|
||||
@ -265,11 +265,11 @@ JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGDMatrixNumRo
|
||||
}
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGBoosterCreate
|
||||
* Signature: ([J)J
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterCreate
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGBoosterCreate
|
||||
(JNIEnv *jenv, jclass jcls, jlongArray jhandles, jlongArray jout) {
|
||||
DMatrixHandle* handles;
|
||||
bst_ulong len = 0;
|
||||
@ -298,11 +298,11 @@ JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterCreat
|
||||
}
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGBoosterFree
|
||||
* Signature: (J)V
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterFree
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGBoosterFree
|
||||
(JNIEnv *jenv, jclass jcls, jlong jhandle) {
|
||||
BoosterHandle handle = (BoosterHandle) jhandle;
|
||||
return XGBoosterFree(handle);
|
||||
@ -310,11 +310,11 @@ JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterFree
|
||||
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGBoosterSetParam
|
||||
* Signature: (JLjava/lang/String;Ljava/lang/String;)V
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterSetParam
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGBoosterSetParam
|
||||
(JNIEnv *jenv, jclass jcls, jlong jhandle, jstring jname, jstring jvalue) {
|
||||
BoosterHandle handle = (BoosterHandle) jhandle;
|
||||
const char* name = jenv->GetStringUTFChars(jname, 0);
|
||||
@ -327,11 +327,11 @@ JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterSetPa
|
||||
}
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGBoosterUpdateOneIter
|
||||
* Signature: (JIJ)V
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterUpdateOneIter
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGBoosterUpdateOneIter
|
||||
(JNIEnv *jenv, jclass jcls, jlong jhandle, jint jiter, jlong jdtrain) {
|
||||
BoosterHandle handle = (BoosterHandle) jhandle;
|
||||
DMatrixHandle dtrain = (DMatrixHandle) jdtrain;
|
||||
@ -339,11 +339,11 @@ JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterUpdat
|
||||
}
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGBoosterBoostOneIter
|
||||
* Signature: (JJ[F[F)V
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterBoostOneIter
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGBoosterBoostOneIter
|
||||
(JNIEnv *jenv, jclass jcls, jlong jhandle, jlong jdtrain, jfloatArray jgrad, jfloatArray jhess) {
|
||||
BoosterHandle handle = (BoosterHandle) jhandle;
|
||||
DMatrixHandle dtrain = (DMatrixHandle) jdtrain;
|
||||
@ -358,11 +358,11 @@ JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterBoost
|
||||
}
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGBoosterEvalOneIter
|
||||
* Signature: (JI[J[Ljava/lang/String;)Ljava/lang/String;
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterEvalOneIter
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGBoosterEvalOneIter
|
||||
(JNIEnv *jenv, jclass jcls, jlong jhandle, jint jiter, jlongArray jdmats, jobjectArray jevnames, jobjectArray jout) {
|
||||
BoosterHandle handle = (BoosterHandle) jhandle;
|
||||
DMatrixHandle* dmats = 0;
|
||||
@ -406,11 +406,11 @@ JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterEvalO
|
||||
}
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGBoosterPredict
|
||||
* Signature: (JJIJ)[F
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterPredict
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGBoosterPredict
|
||||
(JNIEnv *jenv, jclass jcls, jlong jhandle, jlong jdmat, jint joption_mask, jint jntree_limit, jobjectArray jout) {
|
||||
BoosterHandle handle = (BoosterHandle) jhandle;
|
||||
DMatrixHandle dmat = (DMatrixHandle) jdmat;
|
||||
@ -426,11 +426,11 @@ JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterPredi
|
||||
}
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGBoosterLoadModel
|
||||
* Signature: (JLjava/lang/String;)V
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterLoadModel
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGBoosterLoadModel
|
||||
(JNIEnv *jenv, jclass jcls, jlong jhandle, jstring jfname) {
|
||||
BoosterHandle handle = (BoosterHandle) jhandle;
|
||||
const char* fname = jenv->GetStringUTFChars(jfname, 0);
|
||||
@ -441,11 +441,11 @@ JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterLoadM
|
||||
}
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGBoosterSaveModel
|
||||
* Signature: (JLjava/lang/String;)V
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterSaveModel
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGBoosterSaveModel
|
||||
(JNIEnv *jenv, jclass jcls, jlong jhandle, jstring jfname) {
|
||||
BoosterHandle handle = (BoosterHandle) jhandle;
|
||||
const char* fname = jenv->GetStringUTFChars(jfname, 0);
|
||||
@ -457,11 +457,11 @@ JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterSaveM
|
||||
}
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGBoosterLoadModelFromBuffer
|
||||
* Signature: (JJJ)V
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterLoadModelFromBuffer
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGBoosterLoadModelFromBuffer
|
||||
(JNIEnv *jenv, jclass jcls, jlong jhandle, jlong jbuf, jlong jlen) {
|
||||
BoosterHandle handle = (BoosterHandle) jhandle;
|
||||
void *buf = (void*) jbuf;
|
||||
@ -469,11 +469,11 @@ JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterLoadM
|
||||
}
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGBoosterGetModelRaw
|
||||
* Signature: (J)Ljava/lang/String;
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterGetModelRaw
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGBoosterGetModelRaw
|
||||
(JNIEnv * jenv, jclass jcls, jlong jhandle, jobjectArray jout) {
|
||||
BoosterHandle handle = (BoosterHandle) jhandle;
|
||||
bst_ulong len = 0;
|
||||
@ -488,11 +488,11 @@ JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterGetMo
|
||||
}
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_wrapper_XgboostJNI
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGBoosterDumpModel
|
||||
* Signature: (JLjava/lang/String;I)[Ljava/lang/String;
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterDumpModel
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGBoosterDumpModel
|
||||
(JNIEnv *jenv, jclass jcls, jlong jhandle, jstring jfmap, jint jwith_stats, jobjectArray jout) {
|
||||
BoosterHandle handle = (BoosterHandle) jhandle;
|
||||
const char *fmap = jenv->GetStringUTFChars(jfmap, 0);
|
||||
@ -510,4 +510,4 @@ JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_wrapper_XgboostJNI_XGBoosterDumpM
|
||||
|
||||
if (fmap) jenv->ReleaseStringUTFChars(jfmap, (const char *)fmap);
|
||||
return ret;
|
||||
}
|
||||
}
|
||||
221
jvm-packages/xgboost4j/src/native/xgboost4j.h
Normal file
221
jvm-packages/xgboost4j/src/native/xgboost4j.h
Normal file
@ -0,0 +1,221 @@
|
||||
/* DO NOT EDIT THIS FILE - it is machine generated */
|
||||
#include <jni.h>
|
||||
/* Header for class org_dmlc_xgboost4j_XgboostJNI */
|
||||
|
||||
#ifndef _Included_org_dmlc_xgboost4j_XgboostJNI
|
||||
#define _Included_org_dmlc_xgboost4j_XgboostJNI
|
||||
#ifdef __cplusplus
|
||||
extern "C" {
|
||||
#endif
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGBGetLastError
|
||||
* Signature: ()Ljava/lang/String;
|
||||
*/
|
||||
JNIEXPORT jstring JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGBGetLastError
|
||||
(JNIEnv *, jclass);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGDMatrixCreateFromFile
|
||||
* Signature: (Ljava/lang/String;I[J)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGDMatrixCreateFromFile
|
||||
(JNIEnv *, jclass, jstring, jint, jlongArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGDMatrixCreateFromCSR
|
||||
* Signature: ([J[I[F[J)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGDMatrixCreateFromCSR
|
||||
(JNIEnv *, jclass, jlongArray, jintArray, jfloatArray, jlongArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGDMatrixCreateFromCSC
|
||||
* Signature: ([J[I[F[J)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGDMatrixCreateFromCSC
|
||||
(JNIEnv *, jclass, jlongArray, jintArray, jfloatArray, jlongArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGDMatrixCreateFromMat
|
||||
* Signature: ([FIIF[J)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGDMatrixCreateFromMat
|
||||
(JNIEnv *, jclass, jfloatArray, jint, jint, jfloat, jlongArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGDMatrixSliceDMatrix
|
||||
* Signature: (J[I[J)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGDMatrixSliceDMatrix
|
||||
(JNIEnv *, jclass, jlong, jintArray, jlongArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGDMatrixFree
|
||||
* Signature: (J)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGDMatrixFree
|
||||
(JNIEnv *, jclass, jlong);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGDMatrixSaveBinary
|
||||
* Signature: (JLjava/lang/String;I)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGDMatrixSaveBinary
|
||||
(JNIEnv *, jclass, jlong, jstring, jint);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGDMatrixSetFloatInfo
|
||||
* Signature: (JLjava/lang/String;[F)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGDMatrixSetFloatInfo
|
||||
(JNIEnv *, jclass, jlong, jstring, jfloatArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGDMatrixSetUIntInfo
|
||||
* Signature: (JLjava/lang/String;[I)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGDMatrixSetUIntInfo
|
||||
(JNIEnv *, jclass, jlong, jstring, jintArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGDMatrixSetGroup
|
||||
* Signature: (J[I)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGDMatrixSetGroup
|
||||
(JNIEnv *, jclass, jlong, jintArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGDMatrixGetFloatInfo
|
||||
* Signature: (JLjava/lang/String;[[F)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGDMatrixGetFloatInfo
|
||||
(JNIEnv *, jclass, jlong, jstring, jobjectArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGDMatrixGetUIntInfo
|
||||
* Signature: (JLjava/lang/String;[[I)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGDMatrixGetUIntInfo
|
||||
(JNIEnv *, jclass, jlong, jstring, jobjectArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGDMatrixNumRow
|
||||
* Signature: (J[J)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGDMatrixNumRow
|
||||
(JNIEnv *, jclass, jlong, jlongArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGBoosterCreate
|
||||
* Signature: ([J[J)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGBoosterCreate
|
||||
(JNIEnv *, jclass, jlongArray, jlongArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGBoosterFree
|
||||
* Signature: (J)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGBoosterFree
|
||||
(JNIEnv *, jclass, jlong);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGBoosterSetParam
|
||||
* Signature: (JLjava/lang/String;Ljava/lang/String;)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGBoosterSetParam
|
||||
(JNIEnv *, jclass, jlong, jstring, jstring);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGBoosterUpdateOneIter
|
||||
* Signature: (JIJ)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGBoosterUpdateOneIter
|
||||
(JNIEnv *, jclass, jlong, jint, jlong);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGBoosterBoostOneIter
|
||||
* Signature: (JJ[F[F)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGBoosterBoostOneIter
|
||||
(JNIEnv *, jclass, jlong, jlong, jfloatArray, jfloatArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGBoosterEvalOneIter
|
||||
* Signature: (JI[J[Ljava/lang/String;[Ljava/lang/String;)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGBoosterEvalOneIter
|
||||
(JNIEnv *, jclass, jlong, jint, jlongArray, jobjectArray, jobjectArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGBoosterPredict
|
||||
* Signature: (JJIJ[[F)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGBoosterPredict
|
||||
(JNIEnv *, jclass, jlong, jlong, jint, jint, jobjectArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGBoosterLoadModel
|
||||
* Signature: (JLjava/lang/String;)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGBoosterLoadModel
|
||||
(JNIEnv *, jclass, jlong, jstring);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGBoosterSaveModel
|
||||
* Signature: (JLjava/lang/String;)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGBoosterSaveModel
|
||||
(JNIEnv *, jclass, jlong, jstring);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGBoosterLoadModelFromBuffer
|
||||
* Signature: (JJJ)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGBoosterLoadModelFromBuffer
|
||||
(JNIEnv *, jclass, jlong, jlong, jlong);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGBoosterGetModelRaw
|
||||
* Signature: (J[Ljava/lang/String;)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGBoosterGetModelRaw
|
||||
(JNIEnv *, jclass, jlong, jobjectArray);
|
||||
|
||||
/*
|
||||
* Class: org_dmlc_xgboost4j_XgboostJNI
|
||||
* Method: XGBoosterDumpModel
|
||||
* Signature: (JLjava/lang/String;I[[Ljava/lang/String;)I
|
||||
*/
|
||||
JNIEXPORT jint JNICALL Java_org_dmlc_xgboost4j_XgboostJNI_XGBoosterDumpModel
|
||||
(JNIEnv *, jclass, jlong, jstring, jint, jobjectArray);
|
||||
|
||||
#ifdef __cplusplus
|
||||
}
|
||||
#endif
|
||||
#endif
|
||||
@ -0,0 +1,139 @@
|
||||
/*
|
||||
Copyright (c) 2014 by Contributors
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
*/
|
||||
package org.dmlc.xgboost4j;
|
||||
|
||||
import junit.framework.TestCase;
|
||||
import org.apache.commons.logging.Log;
|
||||
import org.apache.commons.logging.LogFactory;
|
||||
import org.junit.Test;
|
||||
|
||||
import java.util.*;
|
||||
import java.util.Map.Entry;
|
||||
|
||||
/**
|
||||
* test cases for Booster
|
||||
*
|
||||
* @author hzx
|
||||
*/
|
||||
public class BoosterImplTest {
|
||||
public static class EvalError implements IEvaluation {
|
||||
private static final Log logger = LogFactory.getLog(EvalError.class);
|
||||
|
||||
String evalMetric = "custom_error";
|
||||
|
||||
public EvalError() {
|
||||
}
|
||||
|
||||
@Override
|
||||
public String getMetric() {
|
||||
return evalMetric;
|
||||
}
|
||||
|
||||
@Override
|
||||
public float eval(float[][] predicts, org.dmlc.xgboost4j.DMatrix dmat) {
|
||||
float error = 0f;
|
||||
float[] labels;
|
||||
try {
|
||||
labels = dmat.getLabel();
|
||||
} catch (XGBoostError ex) {
|
||||
logger.error(ex);
|
||||
return -1f;
|
||||
}
|
||||
int nrow = predicts.length;
|
||||
for (int i = 0; i < nrow; i++) {
|
||||
if (labels[i] == 0f && predicts[i][0] > 0) {
|
||||
error++;
|
||||
} else if (labels[i] == 1f && predicts[i][0] <= 0) {
|
||||
error++;
|
||||
}
|
||||
}
|
||||
|
||||
return error / labels.length;
|
||||
}
|
||||
}
|
||||
|
||||
@Test
|
||||
public void testBoosterBasic() throws XGBoostError {
|
||||
org.dmlc.xgboost4j.DMatrix trainMat = new org.dmlc.xgboost4j.DMatrix("../../demo/data/agaricus.txt.train");
|
||||
org.dmlc.xgboost4j.DMatrix testMat = new org.dmlc.xgboost4j.DMatrix("../../demo/data/agaricus.txt.test");
|
||||
|
||||
//set params
|
||||
Map<String, Object> paramMap = new HashMap<String, Object>() {
|
||||
{
|
||||
put("eta", 1.0);
|
||||
put("max_depth", 2);
|
||||
put("silent", 1);
|
||||
put("objective", "binary:logistic");
|
||||
}
|
||||
};
|
||||
|
||||
//set watchList
|
||||
HashMap<String, org.dmlc.xgboost4j.DMatrix> watches = new HashMap<>();
|
||||
|
||||
watches.put("train", trainMat);
|
||||
watches.put("test", testMat);
|
||||
|
||||
//set round
|
||||
int round = 2;
|
||||
|
||||
//train a boost model
|
||||
Booster booster = XGBoost.train(paramMap, trainMat, round, watches, null, null);
|
||||
|
||||
//predict raw output
|
||||
float[][] predicts = booster.predict(testMat, true);
|
||||
|
||||
//eval
|
||||
IEvaluation eval = new EvalError();
|
||||
//error must be less than 0.1
|
||||
TestCase.assertTrue(eval.eval(predicts, testMat) < 0.1f);
|
||||
|
||||
//test dump model
|
||||
|
||||
}
|
||||
|
||||
/**
|
||||
* test cross valiation
|
||||
*
|
||||
* @throws XGBoostError
|
||||
*/
|
||||
@Test
|
||||
public void testCV() throws XGBoostError {
|
||||
//load train mat
|
||||
org.dmlc.xgboost4j.DMatrix trainMat = new org.dmlc.xgboost4j.DMatrix("../../demo/data/agaricus.txt.train");
|
||||
|
||||
//set params
|
||||
Map<String, Object> param = new HashMap<String, Object>() {
|
||||
{
|
||||
put("eta", 1.0);
|
||||
put("max_depth", 3);
|
||||
put("silent", 1);
|
||||
put("nthread", 6);
|
||||
put("objective", "binary:logistic");
|
||||
put("gamma", 1.0);
|
||||
put("eval_metric", "error");
|
||||
}
|
||||
};
|
||||
|
||||
//do 5-fold cross validation
|
||||
int round = 2;
|
||||
int nfold = 5;
|
||||
//set additional eval_metrics
|
||||
String[] metrics = null;
|
||||
|
||||
String[] evalHist = XGBoost.crossValiation(param, trainMat, round, nfold, metrics,
|
||||
null, null);
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,104 @@
|
||||
/*
|
||||
Copyright (c) 2014 by Contributors
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
*/
|
||||
package org.dmlc.xgboost4j;
|
||||
|
||||
import junit.framework.TestCase;
|
||||
import org.dmlc.xgboost4j.*;
|
||||
import org.junit.Test;
|
||||
|
||||
import java.util.Arrays;
|
||||
import java.util.Random;
|
||||
|
||||
/**
|
||||
* test cases for DMatrix
|
||||
*
|
||||
* @author hzx
|
||||
*/
|
||||
public class DMatrixTest {
|
||||
|
||||
@Test
|
||||
public void testCreateFromFile() throws XGBoostError {
|
||||
//create DMatrix from file
|
||||
org.dmlc.xgboost4j.DMatrix dmat = new org.dmlc.xgboost4j.DMatrix("../../demo/data/agaricus.txt.test");
|
||||
//get label
|
||||
float[] labels = dmat.getLabel();
|
||||
//check length
|
||||
TestCase.assertTrue(dmat.rowNum() == labels.length);
|
||||
//set weights
|
||||
float[] weights = Arrays.copyOf(labels, labels.length);
|
||||
dmat.setWeight(weights);
|
||||
float[] dweights = dmat.getWeight();
|
||||
TestCase.assertTrue(Arrays.equals(weights, dweights));
|
||||
}
|
||||
|
||||
@Test
|
||||
public void testCreateFromCSR() throws XGBoostError {
|
||||
//create Matrix from csr format sparse Matrix and labels
|
||||
/**
|
||||
* sparse matrix
|
||||
* 1 0 2 3 0
|
||||
* 4 0 2 3 5
|
||||
* 3 1 2 5 0
|
||||
*/
|
||||
float[] data = new float[]{1, 2, 3, 4, 2, 3, 5, 3, 1, 2, 5};
|
||||
int[] colIndex = new int[]{0, 2, 3, 0, 2, 3, 4, 0, 1, 2, 3};
|
||||
long[] rowHeaders = new long[]{0, 3, 7, 11};
|
||||
org.dmlc.xgboost4j.DMatrix dmat1 = new org.dmlc.xgboost4j.DMatrix(rowHeaders, colIndex, data, org.dmlc.xgboost4j.DMatrix.SparseType.CSR);
|
||||
//check row num
|
||||
System.out.println(dmat1.rowNum());
|
||||
TestCase.assertTrue(dmat1.rowNum() == 3);
|
||||
//test set label
|
||||
float[] label1 = new float[]{1, 0, 1};
|
||||
dmat1.setLabel(label1);
|
||||
float[] label2 = dmat1.getLabel();
|
||||
TestCase.assertTrue(Arrays.equals(label1, label2));
|
||||
}
|
||||
|
||||
@Test
|
||||
public void testCreateFromDenseMatrix() throws XGBoostError {
|
||||
//create DMatrix from 10*5 dense matrix
|
||||
int nrow = 10;
|
||||
int ncol = 5;
|
||||
float[] data0 = new float[nrow * ncol];
|
||||
//put random nums
|
||||
Random random = new Random();
|
||||
for (int i = 0; i < nrow * ncol; i++) {
|
||||
data0[i] = random.nextFloat();
|
||||
}
|
||||
|
||||
//create label
|
||||
float[] label0 = new float[nrow];
|
||||
for (int i = 0; i < nrow; i++) {
|
||||
label0[i] = random.nextFloat();
|
||||
}
|
||||
|
||||
org.dmlc.xgboost4j.DMatrix dmat0 = new org.dmlc.xgboost4j.DMatrix(data0, nrow, ncol);
|
||||
dmat0.setLabel(label0);
|
||||
|
||||
//check
|
||||
TestCase.assertTrue(dmat0.rowNum() == 10);
|
||||
TestCase.assertTrue(dmat0.getLabel().length == 10);
|
||||
|
||||
//set weights for each instance
|
||||
float[] weights = new float[nrow];
|
||||
for (int i = 0; i < nrow; i++) {
|
||||
weights[i] = random.nextFloat();
|
||||
}
|
||||
dmat0.setWeight(weights);
|
||||
|
||||
TestCase.assertTrue(Arrays.equals(weights, dmat0.getWeight()));
|
||||
}
|
||||
}
|
||||
@ -73,8 +73,8 @@ fi
|
||||
|
||||
if [ ${TASK} == "java_test" ]; then
|
||||
set -e
|
||||
make java
|
||||
cd java
|
||||
make jvm-packages
|
||||
cd jvm-packages
|
||||
./create_wrap.sh
|
||||
cd xgboost4j
|
||||
mvn clean install -DskipTests=true
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user