We don't plan to include any more C++ code in the main scikit-learn code base: libsvm / liblinear is the only exception due to their pervasive use in the ML research community. However we would really encourage more libraries that would follow the sklearn public API (fit / predict / transform) using numpy arrays or scipy sparse matrices as input.
Be aware that the memory layout of the input and output data used internally by libFM is very likely not directly castable as a scipy sparse matrix hence would incur a memory copy hence make it not suitable to address medium scale datasets (e.g. dataset the size of the free memory on a typical workstation). -- Olivier ------------------------------------------------------------------------------ Minimize network downtime and maximize team effectiveness. Reduce network management and security costs.Learn how to hire the most talented Cisco Certified professionals. Visit the Employer Resources Portal http://www.cisco.com/web/learning/employer_resources/index.html _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
