2014/1/16 Joel Nothman <[email protected]>: > There are still issues of whether this is in scikit-learn scope. For > example, does it make sense with sklearn's cross validation? Or will you > want to cross validate on both axes? Given that there is plenty of work to > be done that is well within scikit-learn's scope (prominent alternative > solutions and utilities for problems it already solves), I think this > extension of scope needs to be argued.
+1 I would first focus on generic matrix factorization / completion estimators as unsupervised estimators (using the standard model.fit(X) API with a scipy sparse X). Then real a CF system could leverage such building blocks to build its features in 3rd party libraries that would build upon scikit-learn but would provide the domain specific recsys boilerplate. -- Olivier ------------------------------------------------------------------------------ CenturyLink Cloud: The Leader in Enterprise Cloud Services. Learn Why More Businesses Are Choosing CenturyLink Cloud For Critical Workloads, Development Environments & Everything In Between. Get a Quote or Start a Free Trial Today. http://pubads.g.doubleclick.net/gampad/clk?id=119420431&iu=/4140/ostg.clktrk _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
