model2_cb<-function(widget, window){
  library(e1071)
  library(caret)
  dialog3 <- gtkFileChooserDialog("Choose the Train File", window, "ok",
                                 "gtk-cancel", GtkResponseType["cancel"], "gtk-open",
                                 GtkResponseType["accept"])
  if (dialog3$run() == GtkResponseType["accept"]) {
    df3 <- read.csv(dialog3$getFilename())
    data3<-data.frame(df3)
    dialog3$destroy()
  }
  dialog4 <- gtkFileChooserDialog("Choose the Test FIle", window, "ok",
                                  "gtk-cancel", GtkResponseType["cancel"], "gtk-open",
                                  GtkResponseType["accept"])
  if (dialog4$run() == GtkResponseType["accept"]) {
    df4 <- read.csv(dialog4$getFilename())
    data4<-data.frame(df4)
    dialog4$destroy()
  }
  data4$Class <- "Predicted Value"
  combined <- rbind(data3, data4)
  data4 <- combined[combined$Class == "Predicted Value" ,]
  data3 <- combined[combined$Class != "Actual Value" ,]
  svm.model3 <- svm(Class ~ ., data = data3, cost = 1000, gamma = 1)
  svm.pred3 <- predict(svm.model3, newdata = data4)
  table(pred = svm.pred3, true = data4[,7])
  xtab2<-table(pred = svm.pred3, true = data4[,7])
  confusionMatrix(xtab2)
  y1<-confusionMatrix(xtab2)
  cleanoutput2 <- cbind(df4,svm.pred3)
  colnames(cleanoutput2) <- c("IR","MR","FF","CF","CO","CP","Expected Output","Predicted Output")
  print(cleanoutput2)
  print(y1)
    }