| # |
| # 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. |
| # |
| |
| """ |
| An example demonstrating FPGrowth. |
| Run with: |
| bin/spark-submit examples/src/main/python/ml/fpgrowth_example.py |
| """ |
| # $example on$ |
| from pyspark.ml.fpm import FPGrowth |
| # $example off$ |
| from pyspark.sql import SparkSession |
| |
| if __name__ == "__main__": |
| spark = SparkSession\ |
| .builder\ |
| .appName("FPGrowthExample")\ |
| .getOrCreate() |
| |
| # $example on$ |
| df = spark.createDataFrame([ |
| (0, [1, 2, 5]), |
| (1, [1, 2, 3, 5]), |
| (2, [1, 2]) |
| ], ["id", "items"]) |
| |
| fpGrowth = FPGrowth(itemsCol="items", minSupport=0.5, minConfidence=0.6) |
| model = fpGrowth.fit(df) |
| |
| # Display frequent itemsets. |
| model.freqItemsets.show() |
| |
| # Display generated association rules. |
| model.associationRules.show() |
| |
| # transform examines the input items against all the association rules and summarize the |
| # consequents as prediction |
| model.transform(df).show() |
| # $example off$ |
| |
| spark.stop() |