featuretools.primitives.Skew#
- class featuretools.primitives.Skew[source]#
计算一个分布与正态分布的差异程度.
- Description:
对于正态分布的数据,偏度应约为0. 偏度值 > 0 表示分布的左尾有更多的权重.
Examples
>>> skew = Skew() >>> skew([1, 10, 30, None]) 1.0437603722639681
- __init__()#
Methods
__init__()flatten_nested_input_types(input_types)将嵌套的列模式输入展平成一个列表.
generate_name(base_feature_names, ...)generate_names(base_feature_names, ...)get_args_string()get_arguments()get_description(input_column_descriptions[, ...])get_filepath(filename)get_function()Attributes
base_ofbase_of_excludecommutativedefault_valueDefault value this feature returns if no data found.
description_templateinput_typeswoodwork.ColumnSchema types of inputs
max_stack_depthnameName of the primitive
number_output_featuresNumber of columns in feature matrix associated with this feature
return_typeColumnSchema type of return
stack_onstack_on_excludestack_on_selfuses_calc_time