# SVM - calculating values problem

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## SVM - calculating values problem

 Hello everybody, That is the first time that I am working on a SVM modeling and I would like to calculate by myself the result values from the SVM for each line of my database (named x_appr_svm). First I tested a linear SVM model using the e1071 package and to calculate the individual results by myself I did the next things : Retrieving the model coefficients  : coef_svm<-t(svm\$coefs) %*% x_appr_svm[svm\$index,] Calculating the values for each line : p2<-x_appr_svm %*% t(coef_svm) - svm\$rho Using the predict function to compare : p1<-attr(predict(object=svm, newdata=x_appr_svm, decision.values=T), "decision.values") --> p1 and p2 are the same. Next I tested a polynomial SVM model using the same package and the same method knowing that the model parameters are : degree=2,  gamma=0.02, coef0=0.01 The calculation of the individual values becomes (I guess) : p2<-(0.02*x_appr_svm %*% t(coef_svm)+0.01)^2-svm\$rho --> p1 and p2 are really different! Despite of my searching, I do not understand why or where is the problem in my second p2 formula. Do you see the mistake? Thank you for your help and have a good day, Benoit (France).         [[alternative HTML version deleted]] ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.