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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.
+ */
+
+// scalastyle:off println
+package org.apache.spark.examples.ml
+
+// $example on$
+import org.apache.spark.ml.classification.LinearSVC
+// $example off$
+import org.apache.spark.sql.SparkSession
+
+object LinearSVCExample {
+
+ def main(args: Array[String]): Unit = {
+ val spark = SparkSession
+ .builder
+ .appName("LinearSVCExample")
+ .getOrCreate()
+
+ // $example on$
+ // Load training data
+ val training = spark.read.format("libsvm").load("data/mllib/sample_libsvm_data.txt")
+
+ val lsvc = new LinearSVC()
+ .setMaxIter(10)
+ .setRegParam(0.1)
+
+ // Fit the model
+ val lsvcModel = lsvc.fit(training)
+
+ // Print the coefficients and intercept for linear svc
+ println(s"Coefficients: ${lsvcModel.coefficients} Intercept: ${lsvcModel.intercept}")
+ // $example off$
+
+ spark.stop()
+ }
+}
+// scalastyle:on println