search for: polykernel

...ibrary(RWeka) # Example: no parameter influence mySMO =make_Weka_classifier(name="weka/classifiers/functions/SMO",class=NULL,handlers=list()); # Using control =Weka_control() m1 =mySMO(formula=class~.,data=data[,],control=Weka_control(K="weka.classifiers.functions.supportVector.PolyKernel",E=2)) m2 =mySMO(formula=class~.,data=data[,],control=Weka_control(K="weka.classifiers.functions.supportVector.PolyKernel",E=3)) m3 =mySMO(formula=class~.,data=data[,],control=c("K","weka.classifiers.functions.supportVector.PolyKernel","E",3)) # Us...

Hello, I have two questions concerning the RWeka package: 1.) First question: How can one perform a cross validation, -say 10fold- for a given data set and given model ? 2.) Second question What is the correct syntax for the parametrization of e.g. Kernel classifiers interface m1 <- SMO(Species ~ ., data = iris, control =

...ar(kernel)$sigma 213 ktype <- 2 214 }, 215 "tanhkernel" = 216 { 217 sigma <- kpar(kernel)$scale 218 offset <- kpar(kernel)$offset 219 ktype <- 3 220 }, 221 "polykernel" = 222 { 223 degree <- kpar(kernel)$degree 224 sigma <- kpar(kernel)$scale 225 offset <- kpar(kernel)$offset 226 ktype <- 1 227 }, 228 "vanillakernel" = 229 { 230...