mllib/evaluation/JavaRankingMetricsSuite.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.mllib.evaluation;
0019
0020 import java.io.IOException;
0021 import java.util.Arrays;
0022 import java.util.List;
0023
0024 import scala.Tuple2;
0025 import scala.Tuple2$;
0026
0027 import org.junit.Assert;
0028 import org.junit.Test;
0029
0030 import org.apache.spark.SharedSparkSession;
0031 import org.apache.spark.api.java.JavaRDD;
0032
0033 public class JavaRankingMetricsSuite extends SharedSparkSession {
0034   private transient JavaRDD<Tuple2<List<Integer>, List<Integer>>> predictionAndLabels;
0035
0036   @Override
0037   public void setUp() throws IOException {
0038     super.setUp();
0039     predictionAndLabels = jsc.parallelize(Arrays.asList(
0040       Tuple2$.MODULE$.apply(
0041         Arrays.asList(1, 6, 2, 7, 8, 3, 9, 10, 4, 5), Arrays.asList(1, 2, 3, 4, 5)),
0042       Tuple2$.MODULE$.apply(
0043         Arrays.asList(4, 1, 5, 6, 2, 7, 3, 8, 9, 10), Arrays.asList(1, 2, 3)),
0044       Tuple2$.MODULE$.apply(
0045         Arrays.asList(1, 2, 3, 4, 5), Arrays.<Integer>asList())), 2);
0046   }
0047
0048   @Test
0049   public void rankingMetrics() {
0050     @SuppressWarnings("unchecked")
0051     RankingMetrics<?> metrics = RankingMetrics.of(predictionAndLabels);
0052     Assert.assertEquals(0.355026, metrics.meanAveragePrecision(), 1e-5);
0053     Assert.assertEquals(0.75 / 3.0, metrics.precisionAt(4), 1e-5);
0054   }
0055 }