Overfitting

Overfitting occurs when a model is too complex for the training data. It memorizes the noise in the training set rather than generalizing well. The model performs exceptionally well on the training data but poorly elsewhere. As a result, it fails to make accurate predictions outside of training. This can lead to poor performance and low accuracy on new inputs.