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Jagadeesan authored
## What changes were proposed in this pull request? In Python 3, there is only one integer type (i.e., int), which mostly behaves like the long type in Python 2. Since Python 3 won't accept "L", so removed "L" in all examples. ## How was this patch tested? Unit tests. …rrors] Author: Jagadeesan <as2@us.ibm.com> Closes #15660 from jagadeesanas2/SPARK-18133.
Jagadeesan authored## What changes were proposed in this pull request? In Python 3, there is only one integer type (i.e., int), which mostly behaves like the long type in Python 2. Since Python 3 won't accept "L", so removed "L" in all examples. ## How was this patch tested? Unit tests. …rrors] Author: Jagadeesan <as2@us.ibm.com> Closes #15660 from jagadeesanas2/SPARK-18133.
gaussian_mixture_example.py 1.53 KiB
#
# 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
# $example on$
from pyspark.ml.clustering import GaussianMixture
# $example off$
from pyspark.sql import SparkSession
"""
A simple example demonstrating Gaussian Mixture Model (GMM).
Run with:
bin/spark-submit examples/src/main/python/ml/gaussian_mixture_example.py
"""
if __name__ == "__main__":
spark = SparkSession\
.builder\
.appName("GaussianMixtureExample")\
.getOrCreate()
# $example on$
# loads data
dataset = spark.read.format("libsvm").load("data/mllib/sample_kmeans_data.txt")
gmm = GaussianMixture().setK(2).setSeed(538009335)
model = gmm.fit(dataset)
print("Gaussians shown as a DataFrame: ")
model.gaussiansDF.show(truncate=False)
# $example off$
spark.stop()