1 files changed, 0 insertions, 44 deletions
diff --git a/examples/src/main/python/mllib/kernel_density_estimation_example.py b/examples/src/main/python/mllib/kernel_density_estimation_example.py
deleted file mode 100644
index 3e8f7241a4..0000000000
--- a/examples/src/main/python/mllib/kernel_density_estimation_example.py
+++ /dev/null
@@ -1,44 +0,0 @@
-#
-# 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()