That should totally depend on your dataset. Maybe it is an "easy" dataset
and not much regularization is needed.
Maybe use PCA(n_components=2) or an LDA transform to take a look at your
data in 2D. Maybe they are easily linearly separable?
Sklearn does not do any feature selection if you don't as
Hi, Kristen,
there shouldn’t be any internal feature selection going on behind the scenes.
You may want to compare the weight coefficients of your regularized vs
unregularized model, if they are exactly the same, then this would be an
indicator that something funny is going on. Otherwise, it cou
Hi All,
I am trying to understand Python’s code [function ‘_fit_liblinear' in
https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/svm/base.py]
for fitting an L2-logistic regression for a ‘liblinear’ solver. More
specifically, my [approximately balanced class] dataset is such that t
