Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/11108#discussion_r56433747
--- Diff:
examples/src/main/java/org/apache/spark/examples/mllib/JavaHypothesisTestingExample.java
---
@@ -0,0 +1,84 @@
+/*
+ * 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 org.apache.spark.SparkConf;
+import org.apache.spark.api.java.JavaSparkContext;
+
+// $example on$
+import java.util.Arrays;
+
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.mllib.linalg.Matrices;
+import org.apache.spark.mllib.linalg.Matrix;
+import org.apache.spark.mllib.linalg.Vector;
+import org.apache.spark.mllib.linalg.Vectors;
+import org.apache.spark.mllib.regression.LabeledPoint;
+import org.apache.spark.mllib.stat.Statistics;
+import org.apache.spark.mllib.stat.test.ChiSqTestResult;
+// $example off$
+
+public class JavaHypothesisTestingExample {
+ public static void main(String[] args) {
+
+ SparkConf conf = new
SparkConf().setAppName("JavaHypothesisTestingExample");
+ JavaSparkContext jsc = new JavaSparkContext(conf);
+
+ // $example on$
+ // a vector composed of the frequencies of events
+ Vector vec = Vectors.dense(0.1, 0.15, 0.2, 0.3, 0.25);
+
+ // compute the goodness of fit. If a second vector to test against is
not supplied
+ // as a parameter, the test runs against a uniform distribution.
+ ChiSqTestResult goodnessOfFitTestResult = Statistics.chiSqTest(vec);
+ // summary of the test including the p-value, degrees of freedom, test
statistic,
+ // the method used, and the null hypothesis.
+ System.out.println(goodnessOfFitTestResult);
+ System.out.println();
+
+ // Create a contingency matrix ((1.0, 2.0), (3.0, 4.0), (5.0, 6.0))
+ Matrix mat = Matrices.dense(3, 2, new double[]{1.0, 3.0, 5.0, 2.0,
4.0, 6.0});
+
+ // conduct Pearson's independence test on the input contingency matrix
+ ChiSqTestResult independenceTestResult = Statistics.chiSqTest(mat);
+ // summary of the test including the p-value, degrees of freedom...
+ System.out.println(independenceTestResult);
+ System.out.println();
+
+ LabeledPoint p1 = new LabeledPoint(1.0, Vectors.dense(1.0, 0.0, 3.0));
+ LabeledPoint p2 = new LabeledPoint(1.0, Vectors.dense(1.0, 2.0, 0.0));
+ LabeledPoint p3 = new LabeledPoint(-1.0, Vectors.dense(-1.0, 0.0,
-0.5));
+ // an RDD of labeled points
+ JavaRDD<LabeledPoint> obs = jsc.parallelize(Arrays.asList(p1, p2, p3));
--- End diff --
Same here. Embed `new LabelPoint` in `Arrays.asList`.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
