What is Overfitting and how do you prevent it?

What is Overfitting and how do you prevent it?

Approach: Define the model failing to generalize and list common techniques.

Overfitting occurs when a model learns the noise in the training data rather than the underlying pattern. It is prevented by using more data, cross-validation, regularization (L1/L2), pruning (for trees), dropout (for neural networks), or early stopping.

Follow-up: How does cross-validation help?

Key concepts: validation set, early stopping, dropout.