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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 KernelDensity
+# $example off$
+
+if __name__ == "__main__":
+ sc = SparkContext(appName="KernelDensityEstimationExample") # SparkContext
+
+ # $example on$
+ # an RDD of sample data
+ data = sc.parallelize([1.0, 1.0, 1.0, 2.0, 3.0, 4.0, 5.0, 5.0, 6.0, 7.0, 8.0, 9.0, 9.0])
+
+ # Construct the density estimator with the sample data and a standard deviation for the Gaussian
+ # kernels
+ kd = KernelDensity()
+ kd.setSample(data)
+ kd.setBandwidth(3.0)
+
+ # Find density estimates for the given values
+ densities = kd.estimate([-1.0, 2.0, 5.0])
+ # $example off$
+
+ print(densities)
+
+ sc.stop()