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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
# $example on$
from pyspark.ml.clustering import BisectingKMeans
# $example off$
from pyspark.sql import SparkSession
"""
An example demonstrating bisecting k-means clustering.
Run with:
bin/spark-submit examples/src/main/python/ml/bisecting_k_means_example.py
"""
if __name__ == "__main__":
spark = SparkSession\
.builder\
.appName("PythonBisectingKMeansExample")\
.getOrCreate()
# $example on$
# Loads data.
dataset = spark.read.format("libsvm").load("data/mllib/sample_kmeans_data.txt")
# Trains a bisecting k-means model.
bkm = BisectingKMeans().setK(2).setSeed(1)
model = bkm.fit(dataset)
# Evaluate clustering.
cost = model.computeCost(dataset)
print("Within Set Sum of Squared Errors = " + str(cost))
# Shows the result.
print("Cluster Centers: ")
centers = model.clusterCenters()
for center in centers:
print(center)
# $example off$
spark.stop()
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