featuretools.primitives.Entropy#

class featuretools.primitives.Entropy(dropna=False, base=None)[source]#

计算分类列的熵

Description:

给定一个分类列的观测值列表,返回该分布的熵. NaN值可以视为一个单独的类别或被丢弃.

Parameters:

  • dropna (bool) – 是否将NaN值视为一个单独的类别 默认为False.

  • base (float) – 使用的对数底数 默认为e（自然对数）

Examples

>>> pd_entropy = Entropy()
>>> pd_entropy([1, 2, 3, 4])
1.3862943611198906
__init__(dropna=False, base=None)[source]#

Methods

__init__([dropna, base])

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_of

base_of_exclude

commutative

default_value

Default value this feature returns if no data found.

description_template

input_types

woodwork.ColumnSchema types of inputs

max_stack_depth

name

Name of the primitive

number_output_features

Number of columns in feature matrix associated with this feature

return_type

ColumnSchema type of return

stack_on

stack_on_exclude

stack_on_self

uses_calc_time