Failing code

library(e1071)
library(kernlab)

errors <- c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0)

for(i in seq(1,50)) {

enquesta<-read.csv("APA-TEMA7-P1.csv", header=TRUE, sep=",",dec=",")
enquesta["Salary.3"]<-rep(nrow(enquesta), 0)
enquesta$Salary.3[enquesta$Salary == "35k"] <- 2
enquesta$Salary.3[enquesta$Salary %in% c("45k", ">45k")] <- 3
enquesta$Salary.3[is.na(enquesta$Salary.3)] <- 1
enquesta$Salary.3 <- as.factor(enquesta$Salary.3)
L <- 5
K <- 5
tr <- sample(rep(1:nrow(enquesta)),round(.8*nrow(enquesta)))
dades<-enquesta[tr,]
test<-enquesta[-tr,]
vectorC<-c(.25,.5,.75,1)
errorsC <- rep(0, length(vectorC))
for(cross in seq(1,L)) {
  folds <- sample(rep(1:K, length=nrow(dades)), nrow(dades), replace=FALSE)
  for(k in seq(1:K)){
    training <- dades[folds != k,]
    validation <- dades[folds == k,]
    for(i in seq(1,length(vectorC))){
      training.svm<-ksvm(training$Salary.3~., training, C=vectorC[i])
      p <- predict(training.svm, newdata=validation)
      error <- 1 - (sum(diag(table(p, validation$Salary.3)))/length(p))
      errorsC[i] <- errorsC[i] + error
    }
  }
}
errorsC <- errorsC/(L*K)
bestC.index <- which(errorsC == min(errorsC))
ksvm.result<-ksvm(dades$Salary.3~., dades, C=vectorC[bestC.index])
p.result <- predict(ksvm.result, newdata=test)
(error.result <- 1 - (sum(diag(table(p, validation$Salary.3)))/length(p)))

errors[i] <- error.result

}