training
Overfitting
When a model learns the training data too well, including its noise and outliers, resulting in poor performance on new, unseen data. Overfitting occurs when the model memorizes specific examples rather than learning generalizable patterns.
In practice
A model that achieves 99% accuracy on training data but only 60% on test data is likely overfitting.