#

# 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.

#

# $example on$

from pyspark.ml.classification import LinearSVC

# $example off$

from pyspark.sql import SparkSession

if __name__ == "__main__":

spark = SparkSession\

.builder\

.appName("linearSVC Example")\

.getOrCreate()

# $example on$

# Load training data

training = spark.read.format("libsvm").load("data/mllib/sample_libsvm_data.txt")

lsvc = LinearSVC(maxIter=10, regParam=0.1)

# Fit the model

lsvcModel = lsvc.fit(training)

# Print the coefficients and intercept for linear SVC

print("Coefficients: " + str(lsvcModel.coefficients))

print("Intercept: " + str(lsvcModel.intercept))

# $example off$

spark.stop()