Thanks for the explanation. It's helpful.
On Wednesday, 23 October 2013, 2:24, Andreas Mueller <[email protected]> wrote: On 10/22/2013 09:46 PM, ChungHung Liu wrote: > I read following links > > >http://scikit-learn.org/stable/modules/preprocessing.html#encoding-categorical-features > >http://scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.DictVectorizer.html > > It seems that I should use DictVectorizer, but > You could just use ".toarray()" to create a dense matrix (if it is small enough to fit into memory). If the resulting dense matrix does not fit into memory, you currently can't use RandomForests. ------------------------------------------------------------------------------ October Webinars: Code for Performance Free Intel webinars can help you accelerate application performance. Explore tips for MPI, OpenMP, advanced profiling, and more. Get the most from the latest Intel processors and coprocessors. See abstracts and register > http://pubads.g.doubleclick.net/gampad/clk?id=60135991&iu=/4140/ostg.clktrk _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
