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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;
// $example on$
import org.apache.spark.ml.classification.LinearSVC;
import org.apache.spark.ml.classification.LinearSVCModel;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.SparkSession;
// $example off$
public class JavaLinearSVCExample {
public static void main(String[] args) {
SparkSession spark = SparkSession
.builder()
.appName("JavaLinearSVCExample")
.getOrCreate();
// $example on$
// Load training data
Dataset<Row> training = spark.read().format("libsvm")
.load("data/mllib/sample_libsvm_data.txt");
LinearSVC lsvc = new LinearSVC()
.setMaxIter(10)
.setRegParam(0.1);
// Fit the model
LinearSVCModel lsvcModel = lsvc.fit(training);
// Print the coefficients and intercept for LinearSVC
System.out.println("Coefficients: "
+ lsvcModel.coefficients() + " Intercept: " + lsvcModel.intercept());
// $example off$
spark.stop();
}
}
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