Hi Pablo, I am not sure re-implementing a new criterion is what you are looking for. Criteria are made to evaluate the goodness of a split (i.e., a binary partition of the samples in the current node) in terms of impurity with regards to the output variable - not the inputs.
What you should do instead, I think, is to write a new Splitter implementation for partitioning your samples on the basis of circular features. Then, once your samples are partitioned into two subsets, you can evaluate the goodness of the split using one of our (existing) criteria (no matter how you have found this partition). Hope this can help in your design. Gilles On 29 January 2014 10:21, Lars Buitinck <larsm...@gmail.com> wrote: > 2014-01-29 Pablo Rozas Larraondo <p.rozas.larrao...@gmail.com>: >> Suppose I want to create a regression tree accepting both continuous linear >> data and circular data. If I implement a new RegressionCriterion specific >> for circular data, how difficult would it be to grow a tree combining to >> different Criterions (ie MSE and the new CircularCriterion)? >> >> I suppose the main complexity will come having to tag my variables as >> [normal, circular] to be treated by the appropriate Criterion, but how >> difficult this might be? > > We don't have any convention for tagging different types of data at > the moment, except in preprocessing transformers: all data going to > actual estimators is considered continuous linear for simplicity. The > simple solution would be to replace the circular features with their > sine and cosine after projecting them onto the unit circle. > > ------------------------------------------------------------------------------ > WatchGuard Dimension instantly turns raw network data into actionable > security intelligence. It gives you real-time visual feedback on key > security issues and trends. Skip the complicated setup - simply import > a virtual appliance and go from zero to informed in seconds. > http://pubads.g.doubleclick.net/gampad/clk?id=123612991&iu=/4140/ostg.clktrk > _______________________________________________ > Scikit-learn-general mailing list > Scikit-learn-general@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general ------------------------------------------------------------------------------ WatchGuard Dimension instantly turns raw network data into actionable security intelligence. It gives you real-time visual feedback on key security issues and trends. Skip the complicated setup - simply import a virtual appliance and go from zero to informed in seconds. http://pubads.g.doubleclick.net/gampad/clk?id=123612991&iu=/4140/ostg.clktrk _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
