re-structure Java API, add Scala API and consolidate the names of Java/Scala API

jvm-packages/xgboost4j/src/test/java/org/dmlc/xgboost4j/BoosterImplTest.java

@@ -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);
+  }
+}

jvm-packages/xgboost4j/src/test/java/org/dmlc/xgboost4j/DMatrixTest.java

@@ -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()));
+  }
+}