ml/classification/JavaMultilayerPerceptronClassifierSuite.java

0001 /*
0002  * Licensed to the Apache Software Foundation (ASF) under one or more
0003  * contributor license agreements.  See the NOTICE file distributed with
0004  * this work for additional information regarding copyright ownership.
0005  * The ASF licenses this file to You under the Apache License, Version 2.0
0006  * (the "License"); you may not use this file except in compliance with
0007  * the License.  You may obtain a copy of the License at
0008  *
0009  *    http://www.apache.org/licenses/LICENSE-2.0
0010  *
0011  * Unless required by applicable law or agreed to in writing, software
0012  * distributed under the License is distributed on an "AS IS" BASIS,
0013  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
0014  * See the License for the specific language governing permissions and
0015  * limitations under the License.
0016  */
0017
0018 package org.apache.spark.ml.classification;
0019
0020 import java.util.Arrays;
0021 import java.util.List;
0022
0023 import org.junit.Assert;
0024 import org.junit.Test;
0025
0026 import org.apache.spark.SharedSparkSession;
0027 import org.apache.spark.ml.feature.LabeledPoint;
0028 import org.apache.spark.ml.linalg.Vectors;
0029 import org.apache.spark.sql.Dataset;
0030 import org.apache.spark.sql.Row;
0031
0032 public class JavaMultilayerPerceptronClassifierSuite extends SharedSparkSession {
0033
0034   @Test
0035   public void testMLPC() {
0036     List<LabeledPoint> data = Arrays.asList(
0037       new LabeledPoint(0.0, Vectors.dense(0.0, 0.0)),
0038       new LabeledPoint(1.0, Vectors.dense(0.0, 1.0)),
0039       new LabeledPoint(1.0, Vectors.dense(1.0, 0.0)),
0040       new LabeledPoint(0.0, Vectors.dense(1.0, 1.0))
0041     );
0042     Dataset<Row> dataFrame = spark.createDataFrame(data, LabeledPoint.class);
0043
0044     MultilayerPerceptronClassifier mlpc = new MultilayerPerceptronClassifier()
0045       .setLayers(new int[]{2, 5, 2})
0046       .setBlockSize(1)
0047       .setSeed(123L)
0048       .setMaxIter(100);
0049     MultilayerPerceptronClassificationModel model = mlpc.fit(dataFrame);
0050     Dataset<Row> result = model.transform(dataFrame);
0051     List<Row> predictionAndLabels = result.select("prediction", "label").collectAsList();
0052     for (Row r : predictionAndLabels) {
0053       Assert.assertEquals((int) r.getDouble(0), (int) r.getDouble(1));
0054     }
0055   }
0056 }