Thanks a lot for the reply, some comments below
On 07/10/2010 04:11 AM, Steve Lianoglou wrote:
Hi,
On Fri, Jul 9, 2010 at 12:15 PM, manuel.martin
<manuel.mar...@orleans.inra.fr> wrote:
Dear all,
after having calibrated a svm model through the svm() command of the e1071
package, is there a way to
i) represent the modeled relationships between the y and X variables
(response variable vs. predictors)?
Can you explain a bit more ... how do you want them represented?
I was thinking to a simple ŷ = fi(Xi) plot, fi resulting from the fitted
svm model. Xi is the predictor, among the whole set of predictors, X,
one wish to see the relationship with the response.
For boosted regression trees, which I am more familiar with, this is fi
function is estimated by averaging the effects of all predictors but Xi,
and plotting how ŷ varies as Xi does.
Hope this is a bit clearer, Manuel
ii) rank the influence of the predictors used in the model?
One technique that's often/sometimes used is to calculate the SVM's W
vector by using the support vectors along with their learned
weights/alphas.
This comes up every now and again. Here's an older post explaining how
you might do that with the svm model from e1071:
http://article.gmane.org/gmane.comp.lang.r.general/158272/match=w+b+vector+svr
Hope that helps.
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