• LightBGM之Dataset


    最近使用了LightBGM的Dataset,记录一下:

    1.说明:  classlightgbm.Dataset(datalabel=Nonereference=Noneweight=Nonegroup=Noneinit_score=Nonesilent=Falsefeature_name='auto'categorical_feature='auto'params=Nonefree_raw_data=True)

    Bases: object

    Dataset in LightGBM.

    Constract Dataset.

    Parameters:
    • data (stringnumpy arraypandas DataFramescipy.sparse or list of numpy arrays) – Data source of Dataset. If string, it represents the path to txt file.
    • label (listnumpy 1-D arraypandas one-column DataFrame/Series or Noneoptional (default=None)) – Label of the data.
    • reference (Dataset or Noneoptional (default=None)) – If this is Dataset for validation, training data should be used as reference.
    • weight (listnumpy 1-D arraypandas Series or Noneoptional (default=None)) – Weight for each instance.
    • group (listnumpy 1-D arraypandas Series or Noneoptional (default=None)) – Group/query size for Dataset.
    • init_score (listnumpy 1-D arraypandas Series or Noneoptional (default=None)) – Init score for Dataset.
    • silent (booloptional (default=False)) – Whether to print messages during construction.
    • feature_name (list of strings or 'auto'optional (default="auto")) – Feature names. If ‘auto’ and data is pandas DataFrame, data columns names are used.
    • categorical_feature (list of strings or int, or 'auto'optional (default="auto")) – Categorical features. If list of int, interpreted as indices. If list of strings, interpreted as feature names (need to specify feature_name as well). If ‘auto’ and data is pandas DataFrame, pandas categorical columns are used. All values in categorical features should be less than int32 max value (2147483647). All negative values in categorical features will be treated as missing values.
    • params (dict or Noneoptional (default=None)) – Other parameters.
    • free_raw_data (booloptional (default=True)) – If True, raw data is freed after constructing inner Dataset.

      输出是一个dataset对象

    2.使用:

      根据说明使用自己的数据,我这里data和label都用了DataFrame格式的

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  • 原文地址:https://www.cnblogs.com/demo-deng/p/9613259.html
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