rePLS 0.0.3

Residual Partial Least Squares Learning

rePLS

Examples

from rePLS import rePLS, rePCR, reMLR

import numpy as np



n_samples, n_features, n_outcomes, n_confounders = 100, 10,5,2

n_components = 2

rng = np.random.RandomState(0)



Y = rng.randn(n_samples,n_outcomes)

X = rng.randn(n_samples, n_features)

Z = rng.randn(n_samples, n_confounders)



reg = rePLS(Z=Z,n_components=n_components)

reg.fit(X,Y)

Y_pred = reg.predict(X,Z)