[R] interpretation of svm models with the e1071 package

[manuel.martin]

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.martin at 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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