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diff --git a/examples/src/main/python/mllib/hypothesis_testing_kolmogorov_smirnov_test_example.py b/examples/src/main/python/mllib/hypothesis_testing_kolmogorov_smirnov_test_example.py
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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.
-#
-
-from __future__ import print_function
-
-from pyspark import SparkContext
-# $example on$
-from pyspark.mllib.stat import Statistics
-# $example off$
-
-if __name__ == "__main__":
- sc = SparkContext(appName="HypothesisTestingKolmogorovSmirnovTestExample")
-
- # $example on$
- parallelData = sc.parallelize([0.1, 0.15, 0.2, 0.3, 0.25])
-
- # run a KS test for the sample versus a standard normal distribution
- testResult = Statistics.kolmogorovSmirnovTest(parallelData, "norm", 0, 1)
- # summary of the test including the p-value, test statistic, and null hypothesis
- # if our p-value indicates significance, we can reject the null hypothesis
- # Note that the Scala functionality of calling Statistics.kolmogorovSmirnovTest with
- # a lambda to calculate the CDF is not made available in the Python API
- print(testResult)
- # $example off$
-
- sc.stop()