From 051c6a066f7b5fcc7472412144c15b50a5319bd5 Mon Sep 17 00:00:00 2001 From: Xusen Yin Date: Wed, 9 Dec 2015 12:00:48 -0800 Subject: [SPARK-11551][DOC] Replace example code in ml-features.md using include_example PR on behalf of somideshmukh, thanks! Author: Xusen Yin Author: somideshmukh Closes #10219 from yinxusen/SPARK-11551. --- examples/src/main/python/ml/normalizer_example.py | 43 +++++++++++++++++++++++ 1 file changed, 43 insertions(+) create mode 100644 examples/src/main/python/ml/normalizer_example.py (limited to 'examples/src/main/python/ml/normalizer_example.py') diff --git a/examples/src/main/python/ml/normalizer_example.py b/examples/src/main/python/ml/normalizer_example.py new file mode 100644 index 0000000000..d490221474 --- /dev/null +++ b/examples/src/main/python/ml/normalizer_example.py @@ -0,0 +1,43 @@ +# +# 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 +from pyspark.sql import SQLContext +# $example on$ +from pyspark.ml.feature import Normalizer +# $example off$ + +if __name__ == "__main__": + sc = SparkContext(appName="NormalizerExample") + sqlContext = SQLContext(sc) + + # $example on$ + dataFrame = sqlContext.read.format("libsvm").load("data/mllib/sample_libsvm_data.txt") + + # Normalize each Vector using $L^1$ norm. + normalizer = Normalizer(inputCol="features", outputCol="normFeatures", p=1.0) + l1NormData = normalizer.transform(dataFrame) + l1NormData.show() + + # Normalize each Vector using $L^\infty$ norm. + lInfNormData = normalizer.transform(dataFrame, {normalizer.p: float("inf")}) + lInfNormData.show() + # $example off$ + + sc.stop() -- cgit v1.2.3