What is the best way to prepare interactions of categorical features before fitting with scikit-learn?
statsmodels I could conveniently say in R-style
smf.ols(formula = 'depvar ~ C(var1)*C(var2)', data=df).fit() (same in Stata with
regress depvar i.var1##i.var2).
sklearn.preprocessing.PolynomialFeatures (in v0.15, currently dev) be used with categorical variables?