Hi all. I have a couple of questions about the demo image for the AdaBoost classifier in the dev branch: http://scikit-learn.org/dev/auto_examples/ensemble/plot_forest_iris.html
I've worked through the underlying code, I understand what's being plotted, I think the AdaBoost example (final column) is in error. I figured checking my reasoning made sense before filing a bug report (I have some possible patches too). The first column is for a DecisionTree (with no limits on tree depth), the plot makes sense. The second and third columns are for a RandomForest and ExtraTrees classifier (with DecisionTrees with no depth limit). The plots for columns 2 and 3 are made by iterating over the 30 classifiers and plotting each decision surface with an alpha of 0.1. The fourth column is for an AdaBoost classifier using a DecisionTree with no limit on max depth. The plots in this column don't look right - the red regions clearly encompass where the yellow dots are drawn (this is particularly obvious in the bottom-right plot). The problem is that the weights for the ensemble of classifiers in AdaBoost aren't taken into account, I believe the alpha value for the plot should use these weights. This raises another problem but let me check first - does my logic (weights being required for the plot to make sense) sound ok? Checking clf.score (and calling clf.predict in the yellow regions) show that the underlying classifications are correct (in the yellow regions with AdaBoost the yellow class is chosen). I'm pretty confident it is just the display that's in error. I guess possibly the display is meant to force the user to question why the classifications look wrong and to reason about the weights in AdaBoost, but I'm probably overthinking this! Regards, Ian. -- Ian Ozsvald (A.I. researcher) i...@ianozsvald.com http://IanOzsvald.com http://MorConsulting.com/ http://Annotate.IO http://SocialTiesApp.com/ http://TheScreencastingHandbook.com http://FivePoundApp.com/ http://twitter.com/IanOzsvald http://ShowMeDo.com ------------------------------------------------------------------------------ This SF.net email is sponsored by Windows: Build for Windows Store. http://p.sf.net/sfu/windows-dev2dev _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
