CODEWITHSUNDEEP
pythonscipyregression
paveltr
paveltr

Reputation: 474

scipy PLS getting the regression equation

I made a regression

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)

Then i have coefficients

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

I was looking for an equations for Y1 and Y2.

I checked 

Y1 = coeffs [0] * X1 + coeffs [1] * X2 + coeffs [2] * X2

But it is not equal to pls2.predict

Also I tried to apply pls2.x_weights_, but still no success.

How can I get equation for Y1 and Y2 ?

Upvotes: 0

Views: 764

Answers (1)

paveltr
paveltr

Reputation: 474

I went to predict method and found the solution. {} - means vectors

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

Upvotes: 2

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