Regularization, Overfitting, Dropout Regularization, Early Stopping, Elastic Net.
can use regularization to make the model generalize better. You should use regularization if the gap in performance between train and test is big. This means the model grasps too much details of the train set. Overfitting is related to high variance, which means the model is sensitive to specific