[Pkg-exppsy-maintainers] Q: Crossvalidation feature selection
Per B. Sederberg
persed at princeton.edu
Sat Dec 29 14:56:49 UTC 2007
Hellooo Yarik!
On Dec 24, 2007 4:08 PM, Yaroslav Halchenko <debian at onerussian.com> wrote:
> Hi Per,
>
> And Merry Christmass!
>
And a Merry X-masses to you, too! You have sent me a great present :)
I've prepared my datasets and am ready to try all this out. I've
updated to the latest version of pymvpa and I'll let you know how it
goes.
Latros,
P
> > > In any case, Michael would correct me if I am wrong, by now we didn't
> > > yet have a Classifier which would do some feature selection, ie you had
> > > to implement loop through the splits manually and run RFE
> > > FeatureSelection (using some SensitivityAnalyzer such as OnewayAnova or
> > > LinearSVMWeights if you use SVM) on each split manually.
> > OK, I can certainly do that loop and keep track of the results myself.
> > I just thought some version may already be there (and I see it may be
> > soon :))
> oki doki -- it is accomplished to some degree ;-)
>
> I really hate naming of classifiers we have now, so a bit of refactoring
> will be needed to make them sane. If you have any suggestion -- please
> don't hesitate to share
>
> Ok -- we have few new classifiers and sensitivity selections. First let
> me describe FeatureSelection's:
>
> SensitivityBasedFeatureSelection -- just basic one, alike 1 step RFE --
> ie it just removes some features based on results of some
> SensitivityAnalyzer.
>
> FeatureSelectionPipeline -- which is to
> apply a list of FeatureSelection algorithms (like first remove 50% of
> silent according to ANOVA, and do SVM-sensitivity based RFE on the
> rest))
>
> Now we come to the classifier you wanted:
>
> FeatureSelectionClassifier -- given a base classifier and
> FeatureSelection (like one from above) - create a classifier which
> first does feature selection and then trains, and predicts using only
> selected features.
>
>
> I've done just basic testing, so it still might have bugs. Also I really
> want to discuss with Michael and maybe to come up with some better
> naming convention. May be simply shorten the names of the classes: like
> every Classifier-derived class simply has Clf suffix, the same for
> FeatureSelection to have FS, etc.
>
> > I'm working on an analysis right now that could easily be generalized
> > into an example once this classifier is in there. Let me know when
> > you want me to try it out.
> please do ;-)
>
>
>
>
> --
> Yaroslav Halchenko
> Research Assistant, Psychology Department, Rutgers-Newark
> Student Ph.D. @ CS Dept. NJIT
> Office: (973) 353-5440x263 | FWD: 82823 | Fax: (973) 353-1171
> 101 Warren Str, Smith Hall, Rm 4-105, Newark NJ 07102
> WWW: http://www.linkedin.com/in/yarik
>
>
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