# How to correctly interpret f-regression values during feature selection

I am new to machine learning. I would like to know how correctly interpret Scikit_learn's f_regression values, in order to perform a good feature selection (I'm using f_regression as score function of SelectKBest()). More precisely: is a feature with a high value always better than one with a lower value? How have I to interpret f-regression's values when I am using categorical variables?

selector = feature_selection.SelectPercentile(feature_selection.f_regression, percentile=30)