|
||||
0001 # 0002 # Licensed to the Apache Software Foundation (ASF) under one or more 0003 # contributor license agreements. See the NOTICE file distributed with 0004 # this work for additional information regarding copyright ownership. 0005 # The ASF licenses this file to You under the Apache License, Version 2.0 0006 # (the "License"); you may not use this file except in compliance with 0007 # the License. You may obtain a copy of the License at 0008 # 0009 # http://www.apache.org/licenses/LICENSE-2.0 0010 # 0011 # Unless required by applicable law or agreed to in writing, software 0012 # distributed under the License is distributed on an "AS IS" BASIS, 0013 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 0014 # See the License for the specific language governing permissions and 0015 # limitations under the License. 0016 # 0017 0018 from __future__ import print_function 0019 0020 # $example on$ 0021 from pyspark.ml.feature import RobustScaler 0022 # $example off$ 0023 from pyspark.sql import SparkSession 0024 0025 if __name__ == "__main__": 0026 spark = SparkSession\ 0027 .builder\ 0028 .appName("RobustScalerExample")\ 0029 .getOrCreate() 0030 0031 # $example on$ 0032 dataFrame = spark.read.format("libsvm").load("data/mllib/sample_libsvm_data.txt") 0033 scaler = RobustScaler(inputCol="features", outputCol="scaledFeatures", 0034 withScaling=True, withCentering=False, 0035 lower=0.25, upper=0.75) 0036 0037 # Compute summary statistics by fitting the RobustScaler 0038 scalerModel = scaler.fit(dataFrame) 0039 0040 # Transform each feature to have unit quantile range. 0041 scaledData = scalerModel.transform(dataFrame) 0042 scaledData.show() 0043 # $example off$ 0044 0045 spark.stop()
[ Source navigation ] | [ Diff markup ] | [ Identifier search ] | [ general search ] |
This page was automatically generated by the 2.1.0 LXR engine. The LXR team |