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SnappyData distributed data store and execution engine
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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,
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* See the License for the specific language governing permissions and
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package org.apache.spark.examples.ml;
// $example on$
import java.util.Arrays;
import java.util.List;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.ml.regression.AFTSurvivalRegression;
import org.apache.spark.ml.regression.AFTSurvivalRegressionModel;
import org.apache.spark.mllib.linalg.*;
import org.apache.spark.sql.DataFrame;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.RowFactory;
import org.apache.spark.sql.SQLContext;
import org.apache.spark.sql.types.*;
// $example off$
public class JavaAFTSurvivalRegressionExample {
public static void main(String[] args) {
SparkConf conf = new SparkConf().setAppName("JavaAFTSurvivalRegressionExample");
JavaSparkContext jsc = new JavaSparkContext(conf);
SQLContext jsql = new SQLContext(jsc);
// $example on$
List data = Arrays.asList(
RowFactory.create(1.218, 1.0, Vectors.dense(1.560, -0.605)),
RowFactory.create(2.949, 0.0, Vectors.dense(0.346, 2.158)),
RowFactory.create(3.627, 0.0, Vectors.dense(1.380, 0.231)),
RowFactory.create(0.273, 1.0, Vectors.dense(0.520, 1.151)),
RowFactory.create(4.199, 0.0, Vectors.dense(0.795, -0.226))
);
StructType schema = new StructType(new StructField[]{
new StructField("label", DataTypes.DoubleType, false, Metadata.empty()),
new StructField("censor", DataTypes.DoubleType, false, Metadata.empty()),
new StructField("features", new VectorUDT(), false, Metadata.empty())
});
DataFrame training = jsql.createDataFrame(data, schema);
double[] quantileProbabilities = new double[]{0.3, 0.6};
AFTSurvivalRegression aft = new AFTSurvivalRegression()
.setQuantileProbabilities(quantileProbabilities)
.setQuantilesCol("quantiles");
AFTSurvivalRegressionModel model = aft.fit(training);
// Print the coefficients, intercept and scale parameter for AFT survival regression
System.out.println("Coefficients: " + model.coefficients() + " Intercept: "
+ model.intercept() + " Scale: " + model.scale());
model.transform(training).show(false);
// $example off$
jsc.stop();
}
}
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