What is the correct procedure for using a validation set to reduce overfitting?
Say I split the data 80:10:10 (training: validation:test). I train on the training set then get 90% accuracy. I apply this model to the validation set then get 20%. What do I do then?
How can the validation set be used to reduce overfitting especially with reference to Naïve Bayes?