Re: Important features for each fold

> On Feb 14, 2023, at 1:58 AM, Eibe Frank <[email protected]> wrote:
> 
> If you use the AttributeSelectedClassifier, you will be able to set whatever attribute selection scheme you want as an option in that classifier. The selected attributes would then be passed to ZeroR (if you set that as the base classifier in AttributeSelectedClassifier). The process would be pointless from a classification point-of-view, but you would see the selected attributes in the textual description that is generated.
> 
> Cheers,
> Eibe
> 

Thanks. I hadn’t looked at the attribute selection for some time. That does give you a very good variety of selection criteria.

My thought had been that If you get say accuracy, (I’m not sure this is included in the model,) then for each attribute doing RandomForest you could keep an array of the accuracies of the results for each fold that attribute was included in, using whatever selection criteria RandomForest uses (random?), and then rank importance according to which attributes had the highest mean of their arrays. So which contribute most to the best accuracy? Possibly that already corresponds to what some selection criteria is doing.


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