Overfitting
When a model memorizes the training data too closely, including its noise, and performs poorly on new data. Overfitting is addressed through regularization, dropout, early stopping, and using more diverse training data.
When a model memorizes the training data too closely, including its noise, and performs poorly on new data. Overfitting is addressed through regularization, dropout, early stopping, and using more diverse training data.