Testing for Overfitting in Binary Classifiers

Overfitting (or overtraining) is a common problem for supervised learning models in which learned behavior from a training dataset does not generalize well to an unseen test dataset. The most common cause of overfitting is model complexity (in random forests an example would be using trees with too much depth.) The good news is that […]