Hello
To answer the question, 1st, I have never used SVM-RFE and I just guess what
it is about. Also I do not know which piece of software you are using.
Nevertheless I do not see any reason why features could not be ranked when
using nonlinear kernels. A simple solution might be to try this case with
the software and see if the results are consistent.
Dr.Alwazzi
>From: Monika Ray <[log in to unmask]>
>Reply-To: The Support Vector Machine discussion list
><[log in to unmask]>
>To: [log in to unmask]
>Subject: question about SVM-recursive feature elimination
>Date: Tue, 23 May 2006 21:15:06 -0500
>
>Hello,
>
>I know that one can use SVM-RFE with nonlinear kernels for feature
>extraction. In the linear kernel case, features are ranked by weight and
>features with lower weights are eliminated. Does the same thing happen
>with nonlinear kernels...such as Radial basis function kernel?
>
>Thank You.
>
>Sincerely,
>Monika Ray
>
>***********************************************************************
>The sweetest songs are those that tell of our saddest thought...
>
>Computational Intelligence Centre, Washington University St. louis, MO
>**********************************************************************
_________________________________________________________________
FREE pop-up blocking with the new MSN Toolbar – get it now!
http://toolbar.msn.click-url.com/go/onm00200415ave/direct/01/
|