yunfengzhou-hub commented on code in PR #172: URL: https://github.com/apache/flink-ml/pull/172#discussion_r1022262117
########## flink-ml-python/pyflink/examples/ml/feature/robustscaler_example.py: ########## @@ -0,0 +1,74 @@ +################################################################################ +# 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. +################################################################################ + +# Simple program that creates a RobustScaler instance and uses it for feature +# engineering. + +from pyflink.common import Types +from pyflink.datastream import StreamExecutionEnvironment +from pyflink.table import StreamTableEnvironment + +from pyflink.ml.core.linalg import Vectors, DenseVectorTypeInfo + +from pyflink.ml.lib.feature.robustscaler import RobustScaler + +# Creates a new StreamExecutionEnvironment. +env = StreamExecutionEnvironment.get_execution_environment() + +# Creates a StreamTableEnvironment. +t_env = StreamTableEnvironment.create(env) + +# Generates input training and prediction data. +train_data = t_env.from_data_stream( + env.from_collection([ + (1, Vectors.dense(0.0, 0.0),), + (2, Vectors.dense(1.0, -1.0),), + (3, Vectors.dense(2.0, -2.0),), + (4, Vectors.dense(3.0, -3.0),), + (5, Vectors.dense(4.0, -4.0),), + (6, Vectors.dense(5.0, -5.0),), + (7, Vectors.dense(6.0, -6.0),), + (8, Vectors.dense(7.0, -7.0),), + (9, Vectors.dense(8.0, -8.0),), + ], + type_info=Types.ROW_NAMED( + ['id', 'input'], + [Types.INT(), DenseVectorTypeInfo()]) + )) + +# Creates an RobustScaler object and initializes its parameters. +robust_scaler = RobustScaler()\ + .set_lower(0.25)\ + .set_upper(0.75)\ + .set_relative_error(0.001)\ + .set_with_scaling(True)\ + .set_with_centering(True) + +# Trains the RobustScaler Model. +model = robust_scaler.fit(train_data) + +# Uses the RobustScaler Model for predictions. +output = model.transform(train_data)[0] + +# Extracts and displays the results. Review Comment: Comments in python examples uses the original form of the verbs and do not use uppercase for the first letter. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: issues-unsubscr...@flink.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
