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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.
*/
package org.apache.spark.examples.ml;
import org.apache.spark.sql.SparkSession;
// $example on$
import java.util.Arrays;
import java.util.List;
import org.apache.spark.ml.linalg.Vectors;
import org.apache.spark.ml.linalg.VectorUDT;
import org.apache.spark.ml.stat.ChiSquareTest;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.RowFactory;
import org.apache.spark.sql.types.*;
// $example off$
/**
* An example for Chi-square hypothesis testing.
* Run with
*
* bin/run-example ml.JavaChiSquareTestExample
*
*/
public class JavaChiSquareTestExample {
public static void main(String[] args) {
SparkSession spark = SparkSession
.builder()
.appName("JavaChiSquareTestExample")
.getOrCreate();
// $example on$
List data = Arrays.asList(
RowFactory.create(0.0, Vectors.dense(0.5, 10.0)),
RowFactory.create(0.0, Vectors.dense(1.5, 20.0)),
RowFactory.create(1.0, Vectors.dense(1.5, 30.0)),
RowFactory.create(0.0, Vectors.dense(3.5, 30.0)),
RowFactory.create(0.0, Vectors.dense(3.5, 40.0)),
RowFactory.create(1.0, Vectors.dense(3.5, 40.0))
);
StructType schema = new StructType(new StructField[]{
new StructField("label", DataTypes.DoubleType, false, Metadata.empty()),
new StructField("features", new VectorUDT(), false, Metadata.empty()),
});
Dataset df = spark.createDataFrame(data, schema);
Row r = ChiSquareTest.test(df, "features", "label").head();
System.out.println("pValues: " + r.get(0).toString());
System.out.println("degreesOfFreedom: " + r.getList(1).toString());
System.out.println("statistics: " + r.get(2).toString());
// $example off$
spark.stop();
}
}
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