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Separate Depthwidth and Lossguide growing policy in fast histogram (#4102)

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* add back train method but mark as deprecated

* add back train method but mark as deprecated

* add back train method but mark as deprecated

* fix scalastyle error

* fix scalastyle error

* fix scalastyle error

* fix scalastyle error

* init

* more changes

* temp

* update

* udpate rabit

* change the histogram

* update kfactor

* sync per node stats

* temp

* update

* final

* code clean

* update rabit

* more cleanup

* fix errors

* fix failed tests

* enforce c++11

* broadcast subsampled feature correctly

* init col

* temp

* col sampling

* fix histmastrix init

* fix col sampling

* remove cout

* fix out of bound access

* fix core dump

remove core dump file

* disbale test temporarily

* update

* add fid

* print perf data

* update

* revert some changes

* temp

* temp

* pass all tests

* bring back some tests

* recover some changes

* fix lint issue

* enable monotone and interaction constraints

* don't specify default for monotone and interactions

* recover column init part

* more recovery

* fix core dumps

* code clean

* revert some changes

* fix test compilation issue

* fix lint issue

* resolve compilation issue

* fix issues of lint caused by rebase

* fix stylistic changes and change variable names

* use regtree internal function

* modularize depth width

* address the comments

* fix failed tests

* wrap perf timers with class

* fix lint

* fix num_leaves count

* fix indention

* Update src/tree/updater_quantile_hist.cc

Co-Authored-By: CodingCat <CodingCat@users.noreply.github.com>

* Update src/tree/updater_quantile_hist.h

Co-Authored-By: CodingCat <CodingCat@users.noreply.github.com>

* Update src/tree/updater_quantile_hist.cc

Co-Authored-By: CodingCat <CodingCat@users.noreply.github.com>

* Update src/tree/updater_quantile_hist.cc

Co-Authored-By: CodingCat <CodingCat@users.noreply.github.com>

* Update src/tree/updater_quantile_hist.cc

Co-Authored-By: CodingCat <CodingCat@users.noreply.github.com>

* Update src/tree/updater_quantile_hist.h

Co-Authored-By: CodingCat <CodingCat@users.noreply.github.com>

* merge

* fix compilation
This commit is contained in:
Nan Zhu
2019-02-13 12:56:19 -08:00
committed by GitHub
parent 3be1b9ae30
commit c18a3660fa
8 changed files with 457 additions and 189 deletions
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31
jvm-packages/xgboost4j/src/test/java/ml/dmlc/xgboost4j/java/BoosterImplTest.java
View File

@@ -342,7 +342,6 @@ public class BoosterImplTest {
public void testBoosterEarlyStop() throws XGBoostError, IOException {
DMatrix trainMat = new DMatrix("../../demo/data/agaricus.txt.train");
DMatrix testMat = new DMatrix("../../demo/data/agaricus.txt.test");
// testBoosterWithFastHistogram(trainMat, testMat);
Map<String, Object> paramMap = new HashMap<String, Object>() {
{
put("max_depth", 3);
@@ -375,7 +374,7 @@ public class BoosterImplTest {
}
}
private void testWithFastHisto(DMatrix trainingSet, Map<String, DMatrix> watches, int round,
private void testWithQuantileHisto(DMatrix trainingSet, Map<String, DMatrix> watches, int round,
Map<String, Object> paramMap, float threshold) throws XGBoostError {
float[][] metrics = new float[watches.size()][round];
Booster booster = XGBoost.train(trainingSet, paramMap, round, watches,
@@ -393,10 +392,9 @@ public class BoosterImplTest {
}
@Test
public void testFastHistoDepthWise() throws XGBoostError {
public void testQuantileHistoDepthWise() throws XGBoostError {
DMatrix trainMat = new DMatrix("../../demo/data/agaricus.txt.train");
DMatrix testMat = new DMatrix("../../demo/data/agaricus.txt.test");
// testBoosterWithFastHistogram(trainMat, testMat);
Map<String, Object> paramMap = new HashMap<String, Object>() {
{
put("max_depth", 3);
@@ -410,14 +408,13 @@ public class BoosterImplTest {
Map<String, DMatrix> watches = new HashMap<>();
watches.put("training", trainMat);
watches.put("test", testMat);
testWithFastHisto(trainMat, watches, 10, paramMap, 0.0f);
testWithQuantileHisto(trainMat, watches, 10, paramMap, 0.95f);
}
@Test
public void testFastHistoLossGuide() throws XGBoostError {
public void testQuantileHistoLossGuide() throws XGBoostError {
DMatrix trainMat = new DMatrix("../../demo/data/agaricus.txt.train");
DMatrix testMat = new DMatrix("../../demo/data/agaricus.txt.test");
// testBoosterWithFastHistogram(trainMat, testMat);
Map<String, Object> paramMap = new HashMap<String, Object>() {
{
put("max_depth", 0);
@@ -432,14 +429,13 @@ public class BoosterImplTest {
Map<String, DMatrix> watches = new HashMap<>();
watches.put("training", trainMat);
watches.put("test", testMat);
testWithFastHisto(trainMat, watches, 10, paramMap, 0.0f);
testWithQuantileHisto(trainMat, watches, 10, paramMap, 0.95f);
}
@Test
public void testFastHistoLossGuideMaxBin() throws XGBoostError {
public void testQuantileHistoLossGuideMaxBin() throws XGBoostError {
DMatrix trainMat = new DMatrix("../../demo/data/agaricus.txt.train");
DMatrix testMat = new DMatrix("../../demo/data/agaricus.txt.test");
// testBoosterWithFastHistogram(trainMat, testMat);
Map<String, Object> paramMap = new HashMap<String, Object>() {
{
put("max_depth", 0);
@@ -454,7 +450,7 @@ public class BoosterImplTest {
};
Map<String, DMatrix> watches = new HashMap<>();
watches.put("training", trainMat);
testWithFastHisto(trainMat, watches, 10, paramMap, 0.0f);
testWithQuantileHisto(trainMat, watches, 10, paramMap, 0.95f);
}
@Test
@@ -534,38 +530,33 @@ public class BoosterImplTest {
}
@Test
public void testFastHistoDepthwiseMaxDepth() throws XGBoostError {
public void testQuantileHistoDepthwiseMaxDepth() throws XGBoostError {
DMatrix trainMat = new DMatrix("../../demo/data/agaricus.txt.train");
DMatrix testMat = new DMatrix("../../demo/data/agaricus.txt.test");
// testBoosterWithFastHistogram(trainMat, testMat);
Map<String, Object> paramMap = new HashMap<String, Object>() {
{
put("max_depth", 3);
put("silent", 1);
put("objective", "binary:logistic");
put("tree_method", "hist");
put("max_depth", 2);
put("grow_policy", "depthwise");
put("eval_metric", "auc");
}
};
Map<String, DMatrix> watches = new HashMap<>();
watches.put("training", trainMat);
testWithFastHisto(trainMat, watches, 10, paramMap, 0.85f);
testWithQuantileHisto(trainMat, watches, 10, paramMap, 0.95f);
}
@Test
public void testFastHistoDepthwiseMaxDepthMaxBin() throws XGBoostError {
public void testQuantileHistoDepthwiseMaxDepthMaxBin() throws XGBoostError {
DMatrix trainMat = new DMatrix("../../demo/data/agaricus.txt.train");
DMatrix testMat = new DMatrix("../../demo/data/agaricus.txt.test");
// testBoosterWithFastHistogram(trainMat, testMat);
Map<String, Object> paramMap = new HashMap<String, Object>() {
{
put("max_depth", 3);
put("silent", 1);
put("objective", "binary:logistic");
put("tree_method", "hist");
put("max_depth", 2);
put("max_bin", 2);
put("grow_policy", "depthwise");
put("eval_metric", "auc");
@@ -573,7 +564,7 @@ public class BoosterImplTest {
};
Map<String, DMatrix> watches = new HashMap<>();
watches.put("training", trainMat);
testWithFastHisto(trainMat, watches, 10, paramMap, 0.85f);
testWithQuantileHisto(trainMat, watches, 10, paramMap, 0.95f);
}
/**

32
jvm-packages/xgboost4j/src/test/scala/ml/dmlc/xgboost4j/scala/ScalaBoosterImplSuite.scala
View File

@@ -77,7 +77,7 @@ class ScalaBoosterImplSuite extends FunSuite {
XGBoost.train(trainMat, paramMap, round, watches)
}
private def trainBoosterWithFastHisto(
private def trainBoosterWithQuantileHisto(
trainMat: DMatrix,
watches: Map[String, DMatrix],
round: Int,
@@ -146,57 +146,57 @@ class ScalaBoosterImplSuite extends FunSuite {
XGBoost.crossValidation(trainMat, params, round, nfold)
}
test("test with fast histo depthwise") {
test("test with quantile histo depthwise") {
val trainMat = new DMatrix("../../demo/data/agaricus.txt.train")
val testMat = new DMatrix("../../demo/data/agaricus.txt.test")
val paramMap = List("max_depth" -> "3", "silent" -> "0",
"objective" -> "binary:logistic", "tree_method" -> "hist",
"grow_policy" -> "depthwise", "eval_metric" -> "auc").toMap
trainBoosterWithFastHisto(trainMat, Map("training" -> trainMat, "test" -> testMat),
round = 10, paramMap, 0.0f)
trainBoosterWithQuantileHisto(trainMat, Map("training" -> trainMat, "test" -> testMat),
round = 10, paramMap, 0.95f)
}
test("test with fast histo lossguide") {
test("test with quantile histo lossguide") {
val trainMat = new DMatrix("../../demo/data/agaricus.txt.train")
val testMat = new DMatrix("../../demo/data/agaricus.txt.test")
val paramMap = List("max_depth" -> "0", "silent" -> "0",
"objective" -> "binary:logistic", "tree_method" -> "hist",
"grow_policy" -> "lossguide", "max_leaves" -> "8", "eval_metric" -> "auc").toMap
trainBoosterWithFastHisto(trainMat, Map("training" -> trainMat, "test" -> testMat),
round = 10, paramMap, 0.0f)
trainBoosterWithQuantileHisto(trainMat, Map("training" -> trainMat, "test" -> testMat),
round = 10, paramMap, 0.95f)
}
test("test with fast histo lossguide with max bin") {
test("test with quantile histo lossguide with max bin") {
val trainMat = new DMatrix("../../demo/data/agaricus.txt.train")
val testMat = new DMatrix("../../demo/data/agaricus.txt.test")
val paramMap = List("max_depth" -> "0", "silent" -> "0",
"objective" -> "binary:logistic", "tree_method" -> "hist",
"grow_policy" -> "lossguide", "max_leaves" -> "8", "max_bin" -> "16",
"eval_metric" -> "auc").toMap
trainBoosterWithFastHisto(trainMat, Map("training" -> trainMat),
round = 10, paramMap, 0.0f)
trainBoosterWithQuantileHisto(trainMat, Map("training" -> trainMat),
round = 10, paramMap, 0.95f)
}
test("test with fast histo depthwidth with max depth") {
test("test with quantile histo depthwidth with max depth") {
val trainMat = new DMatrix("../../demo/data/agaricus.txt.train")
val testMat = new DMatrix("../../demo/data/agaricus.txt.test")
val paramMap = List("max_depth" -> "0", "silent" -> "0",
"objective" -> "binary:logistic", "tree_method" -> "hist",
"grow_policy" -> "depthwise", "max_leaves" -> "8", "max_depth" -> "2",
"eval_metric" -> "auc").toMap
trainBoosterWithFastHisto(trainMat, Map("training" -> trainMat),
round = 10, paramMap, 0.85f)
trainBoosterWithQuantileHisto(trainMat, Map("training" -> trainMat),
round = 10, paramMap, 0.95f)
}
test("test with fast histo depthwidth with max depth and max bin") {
test("test with quantile histo depthwidth with max depth and max bin") {
val trainMat = new DMatrix("../../demo/data/agaricus.txt.train")
val testMat = new DMatrix("../../demo/data/agaricus.txt.test")
val paramMap = List("max_depth" -> "0", "silent" -> "0",
"objective" -> "binary:logistic", "tree_method" -> "hist",
"grow_policy" -> "depthwise", "max_depth" -> "2", "max_bin" -> "2",
"eval_metric" -> "auc").toMap
trainBoosterWithFastHisto(trainMat, Map("training" -> trainMat),
round = 10, paramMap, 0.85f)
trainBoosterWithQuantileHisto(trainMat, Map("training" -> trainMat),
round = 10, paramMap, 0.95f)
}
test("test training from existing model in scala") {