最小最大规范化

概述

将数据集指定的某些数字列，转换到一定的数值范围（例如0和1之间）。

输入

输出

数据集

参数说明

样例

inputs = {
    "dataframe": None  # @input {"label":"dataframe","type":"DataFrame"}
}
params = {
    "inputs": inputs,
    "b_output_action": True,
    "outer_pipeline_stages": None,
    "input_features_str": "",  # @param {"label":"input_features_str","type":"string","required":"false","helpTip":""}
    "min": 0.0,  # @param {"label": "min","type":"number","required":"true","range":"(none,none)","helpTip":""}
    "max": 1.0,  # @param {"label":"max","type":"number","required":"true","range":"(none,none)","helpTip":""}
    "input_vector_column": "input_features",  # @param {"label":"input_vector_column","type":"string","required":"true","helpTip":""} 
    "output_vector_column": "minmax_scaler_features"  # @param {"label":"output_vector_column","type":"string","required":"true","helpTip":""} 
}
min_max_scaler____id___ = MLSMinMaxScaler(**params)
min_max_scaler____id___.run()
# @output {"label":"pipeline_model","name":"min_max_scaler____id___.get_outputs()['output_port_1']","type":"PipelineModel"} 
# @output {"label":"dataframe","name":"min_max_scaler____id___.get_outputs()['output_port_2']","type":"DataFrame"}