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Diffstat (limited to 'examples/src/main/python/mllib/normalizer_example.py')
-rw-r--r-- | examples/src/main/python/mllib/normalizer_example.py | 52 |
1 files changed, 52 insertions, 0 deletions
diff --git a/examples/src/main/python/mllib/normalizer_example.py b/examples/src/main/python/mllib/normalizer_example.py new file mode 100644 index 0000000000..a4e028ca9a --- /dev/null +++ b/examples/src/main/python/mllib/normalizer_example.py @@ -0,0 +1,52 @@ +# +# 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.feature import Normalizer +from pyspark.mllib.util import MLUtils +# $example off$ + +if __name__ == "__main__": + sc = SparkContext(appName="NormalizerExample") # SparkContext + + # $example on$ + data = MLUtils.loadLibSVMFile(sc, "data/mllib/sample_libsvm_data.txt") + labels = data.map(lambda x: x.label) + features = data.map(lambda x: x.features) + + normalizer1 = Normalizer() + normalizer2 = Normalizer(p=float("inf")) + + # Each sample in data1 will be normalized using $L^2$ norm. + data1 = labels.zip(normalizer1.transform(features)) + + # Each sample in data2 will be normalized using $L^\infty$ norm. + data2 = labels.zip(normalizer2.transform(features)) + # $example off$ + + print("data1:") + for each in data1.collect(): + print(each) + + print("data2:") + for each in data2.collect(): + print(each) + + sc.stop() |