Hi Ola.
Can you please raise an issue on the issue tracker, preferably with code and data to reproduce? If you can't share your data, see if you can reproduce the issue with synthetic data.

Best,
Andy

On 12/02/2015 10:34 AM, Ola Pawluczyk wrote:
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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