2011/11/17 Lars Buitinck <[email protected]>: > 2011/11/16 Olivier Grisel <[email protected]>: >> You should never use dense matrices: either scipy.sparse or numpy >> arrays. For text data, you should probably stick to estimators that >> work on scipy.sparse input. > > In the current release. > >> Always use X.toarray() if you really need to materialize a dense >> representation of a sparse dataset. X.todense() is a trap. > > The next release will add support for samples in np.matrix objects, though.
Even if scikit-learn will be less broken w.r.t. np.matrix object I would still advise anybody not to use the np.matrix datastructure as it's API is often more misleading than helpful. -- Olivier http://twitter.com/ogrisel - http://github.com/ogrisel ------------------------------------------------------------------------------ All the data continuously generated in your IT infrastructure contains a definitive record of customers, application performance, security threats, fraudulent activity, and more. Splunk takes this data and makes sense of it. IT sense. And common sense. http://p.sf.net/sfu/splunk-novd2d _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
