Issue is here https://github.com/scikit-learn/scikit-learn/issues/2133
2013/7/7 Peter Prettenhofer <peter.prettenho...@gmail.com>
>
>
>
> 2013/7/7 Ian Ozsvald <i...@ianozsvald.com>
>
>> 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)
>> i...@ianozsvald.com
>>
>> http://IanOzsvald.com
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>>
>>
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>
>
>
> --
> Peter Prettenhofer
>
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Peter Prettenhofer
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