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[Blocking][jvm-packages] fix the early stopping feature (#3808)

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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

* add back train method but mark as deprecated

* fix scalastyle error

* fix scalastyle error

* fix scalastyle error

* fix scalastyle error

* temp

* add method for classifier and regressor

* update tutorial

* address the comments

* update
This commit is contained in:
Nan Zhu
2018-10-23 14:53:13 -07:00
committed by GitHub
parent e26b5d63b2
commit 4ae225a08d
7 changed files with 134 additions and 14 deletions
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61
jvm-packages/xgboost4j/src/test/java/ml/dmlc/xgboost4j/java/BoosterImplTest.java
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@@ -152,6 +152,66 @@ public class BoosterImplTest {
}
}
@Test
public void testDescendMetrics() {
Map<String, Object> paramMap = new HashMap<String, Object>() {
{
put("max_depth", 3);
put("silent", 1);
put("objective", "binary:logistic");
put("maximize_evaluation_metrics", "false");
}
};
float[][] metrics = new float[1][5];
for (int i = 0; i < 5; i++) {
metrics[0][i] = i;
}
boolean onTrack = XGBoost.judgeIfTrainingOnTrack(paramMap, 5, metrics, 4);
TestCase.assertFalse(onTrack);
for (int i = 0; i < 5; i++) {
metrics[0][i] = 5 - i;
}
onTrack = XGBoost.judgeIfTrainingOnTrack(paramMap, 5, metrics, 4);
TestCase.assertTrue(onTrack);
for (int i = 0; i < 5; i++) {
metrics[0][i] = 5 - i;
}
metrics[0][0] = 1;
metrics[0][2] = 5;
onTrack = XGBoost.judgeIfTrainingOnTrack(paramMap, 5, metrics, 4);
TestCase.assertTrue(onTrack);
}
@Test
public void testAscendMetrics() {
Map<String, Object> paramMap = new HashMap<String, Object>() {
{
put("max_depth", 3);
put("silent", 1);
put("objective", "binary:logistic");
put("maximize_evaluation_metrics", "true");
}
};
float[][] metrics = new float[1][5];
for (int i = 0; i < 5; i++) {
metrics[0][i] = i;
}
boolean onTrack = XGBoost.judgeIfTrainingOnTrack(paramMap, 5, metrics, 4);
TestCase.assertTrue(onTrack);
for (int i = 0; i < 5; i++) {
metrics[0][i] = 5 - i;
}
onTrack = XGBoost.judgeIfTrainingOnTrack(paramMap, 5, metrics, 4);
TestCase.assertFalse(onTrack);
for (int i = 0; i < 5; i++) {
metrics[0][i] = i;
}
metrics[0][0] = 6;
metrics[0][2] = 1;
onTrack = XGBoost.judgeIfTrainingOnTrack(paramMap, 5, metrics, 4);
TestCase.assertTrue(onTrack);
}
@Test
public void testBoosterEarlyStop() throws XGBoostError, IOException {
DMatrix trainMat = new DMatrix("../../demo/data/agaricus.txt.train");
@@ -162,6 +222,7 @@ public class BoosterImplTest {
put("max_depth", 3);
put("silent", 1);
put("objective", "binary:logistic");
put("maximize_evaluation_metrics", "false");
}
};
Map<String, DMatrix> watches = new LinkedHashMap<>();