2.2sklearn.preprocessing.PolynomialFeatures生成交叉特征

Posted 2021-01-11 cjr0707

sklearn.preprocessing.PolynomialFeatures原文

多项式生成函数：sklearn.preprocessing.PolynomialFeatures(degree=2, interaction_only=False, include_bias=True)
参数说明：

• degree：默认为2，多项式次数(就同几元几次方程中的次数一样)
• interaction_only：是否包含单个自变量**n(n>1)特征数据标识，默认为False，为True则表示去除与自己相乘的情况
• include_bias：是否包含偏差标识，默认为True，为False则表示不包含偏差项

import numpy as np
from sklearn.preprocessing import PolynomialFeatures

X = np.arange(6).reshape(3, 2)

X

array([[0, 1],
       [2, 3],
       [4, 5]])

poly = PolynomialFeatures(degree = 2)

poly.fit_transform(X)

array([[ 1.,  0.,  1.,  0.,  0.,  1.],
       [ 1.,  2.,  3.,  4.,  6.,  9.],
       [ 1.,  4.,  5., 16., 20., 25.]])

# 设置参数interaction_only = True，不包含单个自变量****n(n>1)特征数据
poly = PolynomialFeatures(degree = 2, interaction_only = True)

poly.fit_transform(X)

array([[ 1.,  0.,  1.,  0.],
       [ 1.,  2.,  3.,  6.],
       [ 1.,  4.,  5., 20.]])

# 再添加 设置参数include_bias= False，不包含偏差项数据
poly = PolynomialFeatures(degree = 2, interaction_only = True, include_bias=False)

poly.fit_transform(X)

array([[ 0.,  1.,  0.],
       [ 2.,  3.,  6.],
       [ 4.,  5., 20.]])