Hello. I am new to R studio and currently, I'm working on my MSc thesis and to begin the whole process, I should classify a crash data set with different supervised classification methods such as neural net,SVM,knn,rpart or random forest. My biggest problem is even I normalize the data and tune the parameters and split it into train and test dataset and then load it into the script and run the classification, it gives me a very low kappa and a bad confusion matrix!
The data also has equal number of records for each class. I really need help to figure this out.
Thank You.