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Diffstat (limited to 'examples/src/main/python/mllib/correlations_example.py')
| -rw-r--r-- | examples/src/main/python/mllib/correlations_example.py | 48 |
1 files changed, 0 insertions, 48 deletions
diff --git a/examples/src/main/python/mllib/correlations_example.py b/examples/src/main/python/mllib/correlations_example.py deleted file mode 100644 index 66d18f6e5d..0000000000 --- a/examples/src/main/python/mllib/correlations_example.py +++ /dev/null @@ -1,48 +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 - -import numpy as np - -from pyspark import SparkContext -# $example on$ -from pyspark.mllib.stat import Statistics -# $example off$ - -if __name__ == "__main__": - sc = SparkContext(appName="CorrelationsExample") # SparkContext - - # $example on$ - seriesX = sc.parallelize([1.0, 2.0, 3.0, 3.0, 5.0]) # a series - # seriesY must have the same number of partitions and cardinality as seriesX - seriesY = sc.parallelize([11.0, 22.0, 33.0, 33.0, 555.0]) - - # Compute the correlation using Pearson's method. Enter "spearman" for Spearman's method. - # If a method is not specified, Pearson's method will be used by default. - print("Correlation is: " + str(Statistics.corr(seriesX, seriesY, method="pearson"))) - - data = sc.parallelize( - [np.array([1.0, 10.0, 100.0]), np.array([2.0, 20.0, 200.0]), np.array([5.0, 33.0, 366.0])] - ) # an RDD of Vectors - - # calculate the correlation matrix using Pearson's method. Use "spearman" for Spearman's method. - # If a method is not specified, Pearson's method will be used by default. - print(Statistics.corr(data, method="pearson")) - # $example off$ - - sc.stop() |