Hi everybody. I'd like to convert an array of integer categorial features to a sparse indicator matrix. So my data points look like x =[ 100, 1, 5, 10] These are indices for feature-bins which don't really have an ordering. Therefore I want to convert them to a one-hot encoding per feature.
What is the best way in sklearn to achieve this? This looks a bit like the DictVectorizer, I think. But I'd have to convert my array to a dict first, which seems pretty wasteful. Is there a better way in sklearn? If not, do you think this kind of encoding is common enough to be included in sklearn? Cheers, Andy ------------------------------------------------------------------------------ Everyone hates slow websites. So do we. Make your web apps faster with AppDynamics Download AppDynamics Lite for free today: http://p.sf.net/sfu/appdyn_sfd2d_oct _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
