# Applying dimensionality reduction on OneHotEncoded array

I have a really large data set with mixed variables. I have converted categorical variables to numerical using OneHotEncoding and it has resulted in more than a couple of thousand different features, combined that is.

Is it possible to apply dimensionality reduction algorithms on OneHotEncoded data which looks like [[1. 0. 1. 0.]...[0. 0. 0. 0.]] or should it be done by merging with the original data set?

• By the way: Have you performed your one-hot encoding with pd.get_dummies from the pandas package with drop_first=True? That saves you one column per categorical feature without removing any information. Feb 19, 2018 at 14:58
• No @EliasStrehle I haven't. I must try that. Thanks for the tip. Feb 20, 2018 at 17:33