spark-gpu-master/mllib/src/test/java/org/apache/spark/ml/classification/JavaGBTClassifierSuite.java
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 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You 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.
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package org.apache.spark.ml.classification;

import java.io.Serializable;
import java.util.HashMap;
import java.util.Map;

import org.junit.After;
import org.junit.Before;
import org.junit.Test;

import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.ml.impl.TreeTests;
import org.apache.spark.mllib.classification.LogisticRegressionSuite;
import org.apache.spark.mllib.regression.LabeledPoint;
import org.apache.spark.sql.DataFrame;


public class JavaGBTClassifierSuite implements Serializable {

  private transient JavaSparkContext sc;

  @Before
  public void setUp() {
    sc = new JavaSparkContext("local", "JavaGBTClassifierSuite");
  }

  @After
  public void tearDown() {
    sc.stop();
    sc = null;
  }

  @Test
  public void runDT() {
    int nPoints = 20;
    double A = 2.0;
    double B = -1.5;

    JavaRDD<LabeledPoint> data = sc.parallelize(
      LogisticRegressionSuite.generateLogisticInputAsList(A, B, nPoints, 42), 2).cache();
    Map<Integer, Integer> categoricalFeatures = new HashMap<Integer, Integer>();
    DataFrame dataFrame = TreeTests.setMetadata(data, categoricalFeatures, 2);

    // This tests setters. Training with various options is tested in Scala.
    GBTClassifier rf = new GBTClassifier()
      .setMaxDepth(2)
      .setMaxBins(10)
      .setMinInstancesPerNode(5)
      .setMinInfoGain(0.0)
      .setMaxMemoryInMB(256)
      .setCacheNodeIds(false)
      .setCheckpointInterval(10)
      .setSubsamplingRate(1.0)
      .setSeed(1234)
      .setMaxIter(3)
      .setStepSize(0.1)
      .setMaxDepth(2); // duplicate setMaxDepth to check builder pattern
    for (String lossType: GBTClassifier.supportedLossTypes()) {
      rf.setLossType(lossType);
    }
    GBTClassificationModel model = rf.fit(dataFrame);

    model.transform(dataFrame);
    model.totalNumNodes();
    model.toDebugString();
    model.trees();
    model.treeWeights();

    /*
    // TODO: Add test once save/load are implemented.  SPARK-6725
    File tempDir = Utils.createTempDir(System.getProperty("java.io.tmpdir"), "spark");
    String path = tempDir.toURI().toString();
    try {
      model3.save(sc.sc(), path);
      GBTClassificationModel sameModel = GBTClassificationModel.load(sc.sc(), path);
      TreeTests.checkEqual(model3, sameModel);
    } finally {
      Utils.deleteRecursively(tempDir);
    }
    */
  }
}
