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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