scipy PLS获得回归方程

Question

我做了回归

basket.purchase_Date.now.strftime('%Y-%m-%d %H:%M %z')
=> "2016-04-26 22:48 -0400"

然后我有系数

import numpy as np
from sklearn.cross_decomposition import PLSRegression

X = [[0., 0., 1.], [1.,0.,0.], [2.,2.,2.], [2.,5.,4.]]
Y = [[0.1, -0.2], [0.9, 1.1], [6.2, 5.9], [11.9, 12.3]]

pls2 = PLSRegression(n_components=2)
pls2.fit(X, Y)

我正在寻找Y1和Y2的等式。

我检查了

coeffs = pls2.coef_
[[ 1.53732139  1.5363102 ]
 [ 0.97075672  1.0153412 ]
 [ 1.19152707  1.23299069]]

但它不等于Y1 = coeffs [0] * X1 + coeffs [1] * X2 + coeffs [2] * X2

我也试图申请pls2.predict，但仍未成功。

如何获得Y1和Y2的等式？

Answer 1

我去了predict方法并找到了解决方案。 {} - 表示向量

{Y_predicted} = normalized({X}) x pls.coef_ + {Y_o}mean