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0001 /* 0002 * Licensed to the Apache Software Foundation (ASF) under one or more 0003 * contributor license agreements. See the NOTICE file distributed with 0004 * this work for additional information regarding copyright ownership. 0005 * The ASF licenses this file to You under the Apache License, Version 2.0 0006 * (the "License"); you may not use this file except in compliance with 0007 * the License. You may obtain a copy of the License at 0008 * 0009 * http://www.apache.org/licenses/LICENSE-2.0 0010 * 0011 * Unless required by applicable law or agreed to in writing, software 0012 * distributed under the License is distributed on an "AS IS" BASIS, 0013 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 0014 * See the License for the specific language governing permissions and 0015 * limitations under the License. 0016 */ 0017 0018 package org.apache.spark.examples.ml; 0019 0020 // $example on$ 0021 import org.apache.spark.ml.classification.LinearSVC; 0022 import org.apache.spark.ml.classification.LinearSVCModel; 0023 import org.apache.spark.sql.Dataset; 0024 import org.apache.spark.sql.Row; 0025 import org.apache.spark.sql.SparkSession; 0026 // $example off$ 0027 0028 public class JavaLinearSVCExample { 0029 public static void main(String[] args) { 0030 SparkSession spark = SparkSession 0031 .builder() 0032 .appName("JavaLinearSVCExample") 0033 .getOrCreate(); 0034 0035 // $example on$ 0036 // Load training data 0037 Dataset<Row> training = spark.read().format("libsvm") 0038 .load("data/mllib/sample_libsvm_data.txt"); 0039 0040 LinearSVC lsvc = new LinearSVC() 0041 .setMaxIter(10) 0042 .setRegParam(0.1); 0043 0044 // Fit the model 0045 LinearSVCModel lsvcModel = lsvc.fit(training); 0046 0047 // Print the coefficients and intercept for LinearSVC 0048 System.out.println("Coefficients: " 0049 + lsvcModel.coefficients() + " Intercept: " + lsvcModel.intercept()); 0050 // $example off$ 0051 0052 spark.stop(); 0053 } 0054 }
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