Github user yinxusen commented on a diff in the pull request:
https://github.com/apache/spark/pull/9689#discussion_r45316327
--- Diff:
examples/src/main/java/org/apache/spark/examples/mllib/JavaMultiLabelClassificationMetricsExample.java
---
@@ -0,0 +1,79 @@
+/*
+ * 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.
+ */
+package org.apache.spark.examples.mllib;
+
+
+import java.util.Arrays;
+import java.util.List;
+// $example on$
+import scala.Tuple2;
+
+import org.apache.spark.api.java.*;
+import org.apache.spark.mllib.evaluation.MultilabelMetrics;
+import org.apache.spark.rdd.RDD;
+import org.apache.spark.SparkConf;
+// $example off$
+import org.apache.spark.SparkContext;
+
+public class JavaMultiLabelClassificationMetricsExample {
+ public static void main(String[] args) {
+ SparkConf conf = new SparkConf().setAppName("Multilabel Classification
Metrics Example");
+ JavaSparkContext sc = new JavaSparkContext(conf);
+ // $example on$
+ List<Tuple2<double[], double[]>> data = Arrays.asList(
+ new Tuple2<double[], double[]>(new double[]{0.0, 1.0}, new
double[]{0.0, 2.0}),
+ new Tuple2<double[], double[]>(new double[]{0.0, 2.0}, new
double[]{0.0, 1.0}),
+ new Tuple2<double[], double[]>(new double[]{}, new double[]{0.0}),
+ new Tuple2<double[], double[]>(new double[]{2.0}, new double[]{2.0}),
+ new Tuple2<double[], double[]>(new double[]{2.0, 0.0}, new
double[]{2.0, 0.0}),
+ new Tuple2<double[], double[]>(new double[]{0.0, 1.0, 2.0}, new
double[]{0.0, 1.0}),
+ new Tuple2<double[], double[]>(new double[]{1.0}, new double[]{1.0,
2.0})
+ );
+ JavaRDD<Tuple2<double[], double[]>> scoreAndLabels =
sc.parallelize(data);
+
+ // Instantiate metrics object
+ MultilabelMetrics metrics = new
MultilabelMetrics(scoreAndLabels.rdd());
+
+ // Summary stats
+ System.out.format("Recall = %f\n", metrics.recall());
+ System.out.format("Precision = %f\n", metrics.precision());
+ System.out.format("F1 measure = %f\n", metrics.f1Measure());
+ System.out.format("Accuracy = %f\n", metrics.accuracy());
+
+ // Stats by labels
+ for (int i = 0; i < metrics.labels().length - 1; i++) {
+ System.out.format("Class %1.1f precision = %f\n",
metrics.labels()[i], metrics.precision
+ (metrics.labels()[i]));
--- End diff --
2-indention
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