sklearn.preprocessing.PolynomialFeatures原文

多項式生成函數：sklearn.preprocessing.PolynomialFeatures(degree=2, interaction_only=False, include_bias=True)
參數說明：

• degree：默認為2，多項式次數(就同幾元幾次方程中的次數一樣)
• interaction_only：是否包含單個自變量**n(n>1)特征數據標識，默認為False，為True則表示去除與自己相乘的情況
• include_bias：是否包含偏差標識，默認為True，為False則表示不包含偏差項

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.]])
 

# 設置參數interaction_only = True，不包含單個自變量****n(n>1)特征數據
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 設置參數include_bias= False，不包含偏差項數據
poly = PolynomialFeatures(degree = 2, interaction_only = True, include_bias=False)
 

poly.fit_transform(X)

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

2.2sklearn.preprocessing.PolynomialFeatures生成交叉特征