# scikit learn Feature selection for time series forecasting [closed]

heres the link to sklearns feature selection/engineering http://scikit-learn.org/stable/modules/feature_selection.html

I was wondering if these methods are actually useful? I have around 20/30 features (all numerical) in total and was wondering how these methods are able to help?

Shall i perform analysis with and without FS/FE and compare?

• Although wording can be improved, the question is just asking if feature selection is helpful in any situation, specially when there are about 20/30 features. A short answer to that question may be useful to future readers. – Pere Apr 4 '18 at 7:38

If that is the case, then yes, those feature selection methods may be pretty useful, but they're not the only ones you have at hand, and as you see there, they vary a lot and some of them come from training models for the purpose of selecting features, e.g. $L_1$ regularized linear regression, or a tree based feature selection.