[scikit-learn] Sensitivity analysis PR proposal

Hi, Is there a wish to have sensitivity analysis? Currently we can measure the quality of a regressor’s output with a metric, but there is nothing to on the parameter side. It would be handy to have sensitivity measures of the input parameters on the output. Namely: Sobol’ indices (most used).

Re: [scikit-learn] Update or downgrade PCA

n_features)) itime = time.time() [pod._update(snap.T[:, None]) for snap in snapshot3] print(time.time() - itime) itime = time.time() ipca.partial_fit(snapshot3) print(time.time() - itime) np.allclose(ipca.singular_values_[:999], pod.S[:999]) 2018-07-03 11:06 GMT+02:00 Pamphile Roy : > I h

Re: [scikit-learn] Update or downgrade PCA

I have no idea about the comparison with sklearn.decomposition.IncrementalPCA. Was not aware of this but from the code it seems to be a different approach. I will try to come with some numbers. Pamphile ___ scikit-learn mailing list [email protected]

[scikit-learn] Update or downgrade PCA

Hi everyone, I have some code that allows to upgrade (or downgrade) a PCA with a new sample. The update part is handy when you are doing live observations for instance and you want a quick way to update your PCA without having to recompute the whole thing from scratch. Are you interested in this?