I am using some ensemble classifiers such as Random forest for a classification task. I have tried tuning the classifier parameters, but failed to prevent overfitting.
Apart from tuning the parameters , are there any techniques to prepare data in such a way so that it doesn't overfit?
For example, my intuition is that if we divide values of numerical feature into groups, it will give less details thereby tendency to over fit will decrease.
Am I thinking in right direction ?