[Scikit-learn-general] Custom splitting criterion for decision tree classifier

2014-01-12 Thread Caleb
Hi all, In the current implementation of the decision tree, data is split according to the criterion of the form: some feature some threshold Is there a way use more general form such as: some feature = some value or F(feature) some threshold where F is a function of the features. It would be

Re: [Scikit-learn-general] Custom splitting criterion for decision tree classifier

2014-01-12 Thread Lars Buitinck
2014/1/12 Caleb cloverev...@yahoo.com: Is there a way use more general form such as: some feature = some value or F(feature) some threshold where F is a function of the features. You can replace the features with their F values in X for the latter. Any reason not to do that?

Re: [Scikit-learn-general] Custom splitting criterion for decision tree classifier

2014-01-12 Thread Gilles Louppe
Dear Caleb, The current implementation does not allow for that. You can do as suggested by Lars though, if this is practical for you. Gilles On 12 January 2014 16:03, Caleb cloverev...@yahoo.com wrote: Hi all, In the current implementation of the decision tree, data is split according

Re: [Scikit-learn-general] Custom splitting criterion for decision tree classifier

2014-01-12 Thread Juan Nunez-Iglesias
Of course, some feature = some value can also be expressed as F(some feature), so really, moving all of the feature transformation up front should allow you to do everything you suggested. I understand the convenience of using custom functions in some cases, but at least the workaround here is