2. Overfitting is an undesirable machine learning behavior that occurs when the machine learning model gives accurate predictions for training data but not for new data. There are some techniques that could ease or even solve this problem. Which of the following techniques can NOT avoid overfitting problem? (A) Increasing layers / number of units per layer. (B) Using Lasso / Ridge regularization. (C) Early stopping while training model. (D) Adding dropout between layers. (E) Cross-validation.