Hey everybody. Looking a bit into my memory problems, the first thing I noticed is that the "fit" method of BaseDecisionTree converts the data into float32 and Fortran-Style ordering. I haven't paid much attention to that but is that a common pattern? Having float32 seems reasonable and this conversion is also done in the SVMs. But there it is also mentioned explicitly in the docs.
Converting the input to Fortran-style ordering seems a bit weird to me, as I thought the convention was that the data is assumed to be C-ordered. Is there an efficiency reason for doing this that can not be circumvented? Another thing I don't like so much is that the conversion into float32 is not very explicit, since a type is defined in the _tree.pyx, then imported into tree.py and used for conversion there. I no-one disagrees I would very much prefer to make the type explicit in tree.py. Any hints on the Fortran style ordering would be very welcome. Thanks, Andy ------------------------------------------------------------------------------ Write once. Port to many. Get the SDK and tools to simplify cross-platform app development. Create new or port existing apps to sell to consumers worldwide. Explore the Intel AppUpSM program developer opportunity. appdeveloper.intel.com/join http://p.sf.net/sfu/intel-appdev _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
