2013/7/7 Ian Ozsvald <[email protected]>
> 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?
>
I think you are correct - we should definitely fix that - lets create an
issue for that.
>
> 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)
> [email protected]
>
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--
Peter Prettenhofer
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