Hi all, I recently wrote a decision tree viewer in D3 [1] that allows interactive exploring of decision trees - even though its quite a hack (JS is my nemesis) I thought it may be of use for other people as well. You can find the source code in this gist [2] and a demo for iris and boston here [3].
The thickness of a branch indicates the number of training samples that reached the branch. The color encodes the class distribution (for classification) or the mean value (for regression; red means higher, blue lower). Internal nodes that can be expanded are highlighted in light blue. best, Peter [1] http://d3js.org [2] https://gist.github.com/3813537 [3] http://bl.ocks.org/d/3813537/ -- Peter Prettenhofer ------------------------------------------------------------------------------ Got visibility? Most devs has no idea what their production app looks like. Find out how fast your code is with AppDynamics Lite. http://ad.doubleclick.net/clk;262219671;13503038;y? http://info.appdynamics.com/FreeJavaPerformanceDownload.html _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
