Hello all,
I'm doing a PLS regression on spectral data [x.train] with respect to
concentrations of a few substances [y.train], and find that
centering/scaling my data gives me good stats. However, my y_pred_train is
always scaled, and I cannot figure out how to get it back to the unscaled
space.
To make it a bit clearer:
x_train.shape
(40, 904)
y_train.shape
(40, 7)
x_test.shape
(10, 904)
y_test.shape
(10, 7)
pls2 = PLSRegression(copy=True, max_iter=500, n_components=7, scale=True,
tol=1e-06)
pls2.fit(x_train, y_train)
y_pred_train = pls2.predict(x_train)
y_pred_train is always several orders of magnitude larger than y_train. I
tried scaling y_pred_train by pls2.y_mean_ and pls2.y_std_ but I cannot
figure things out. Any help would be greatly appreciated!
Thank you,
Ola
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