FP-growth

概述

“FP-Growth”节点用于挖掘频繁模式，该算法使用了一种称为频繁模式树（Frequent Pattern Tree）的数据结构。FP-tree是一种特殊的前缀树，由频繁项头表和项前缀树构成。FP-Growth算法基于以上的结构加快整个挖掘过程。

输入

输出

数据集和spark pipeline类型的模型

参数说明

样例

inputs = {
    "dataframe": None  # @input {"label":"dataframe","type":"DataFrame"}
}
params = {
    "inputs": inputs,
    "input_features_str": "",  # @param {"label":"input_features_str","type":"string","required":"false","helpTip":""}
    "fp_items_col": "values",  # @param {"label":"fp_items_col","type":"string","required":"false","helpTip":""}
    "prediction_col": "prediction",  # @param {"label":"prediction_col","type":"string","required":"false","helpTip":""}
    "min_support": 0.3,  # @param {"label":"min_support","type":"number","required":"true","range":"(none,none)","helpTip":""}
    "min_confidence": 0.8  # @param {"label":"min_confidence","type":"number","required":"true","range":"(none,none)","helpTip":""}
}
fp_growth____id___ = MLSFPGrowth(**params)
fp_growth____id___.run()
# @output {"label":"pipeline_model","name":"fp_growth____id___.get_outputs()['output_port_1']","type":"PipelineModel"}
# @output {"label":"dataframe","name":"fp_growth____id___.get_outputs()['output_port_2']","type":"DataFrame"}