2013/6/20 Lars Buitinck <[email protected]>: > 2013/6/20 Olivier Grisel <[email protected]>: >>> Actually twice as much, even on a 32-bit platform (float size is >>> always 64 bits). >> >> The decision tree code always uses 32 bits floats: >> >> https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/tree/_tree.pyx#L38 >> >> but you have to cast your data to `dtype=np.float32` in fortran layout >> ahead of time to avoid the memory copy. > > OneHot produces np.float, though, which is float64.
Alright but you could convert it to np.float32 before calling toarray. But anyway this kind of sparsity level is unsuitable for random forests anyways I think. -- Olivier http://twitter.com/ogrisel - http://github.com/ogrisel ------------------------------------------------------------------------------ This SF.net email is sponsored by Windows: Build for Windows Store. http://p.sf.net/sfu/windows-dev2dev _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
