I'm a little confused on how to manage my data set with WEKA (for data mining).
I have a Dat set including 11377 record classified as follows:
- 11111 records have class YES
- 266 records have class NO
This is an unbalanced class, and if I start the classification process with WEKA, the results will be poor.
I want to use the Cross-validation with 10 fold for the classification of data with J48 tree algorithm, but first I need to oversample my minority class? How can I prevent overfitting of data?