2013/4/5 Bill Power <[email protected]>: > i know this is going to sound a little silly, but I was thinking there that > it might be nice to be able to do this with scikit learn > > clf = sklearn.anyClassifier() > clf.fit( { 0: dataWithLabel0, > 1: dataWithLabel1 } ) > > instead of having to separate the data/labels manually. i guess fit would do > that internally, but it might be nice to have this
Many implementations of fit actually work on the current format directly, and converting from your suggested format would be a very costly operation in terms of memory use. It would also make input validation harder, because dataWithLabel0 and dataWithLabel1 would have to have the same number of features, it wouldn't work with precomputed kernels, and it would break the symmetry between classification and regression, which is exploited in some of the training algorithms. In other words, sorry, but we're not going to implement this. -- Lars Buitinck Scientific programmer, ILPS University of Amsterdam ------------------------------------------------------------------------------ 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
