manuel.martin
2010-Jul-09 16:15 UTC
[R] interpretation of svm models with the e1071 package
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)? ii) rank the influence of the predictors used in the model? Right now I am more interested in regression models, but I guess this would be useful for classification too. Thank you in advance, manuel -- ---------------------------- INRA - InfoSol Centre de recherche d'Orl?ans 2163 Avenue de la Pomme de Pin CS 40001 ARDON 45075 ORLEANS Cedex 2 tel : (33) (0)2 38 41 48 21 fax : (33) (0)2 38 41 78 69 http://www.gissol.fr http://bdat.orleans.inra.fr ----0----0------------------
Steve Lianoglou
2010-Jul-10 02:11 UTC
[R] interpretation of svm models with the e1071 package
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?> 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. -- Steve Lianoglou Graduate Student: Computational Systems Biology ?| Memorial Sloan-Kettering Cancer Center ?| Weill Medical College of Cornell University Contact Info: http://cbio.mskcc.org/~lianos/contact