Overfitting

Creating a model that matches the training data so closely that the model fails to make correct predictions on new data. Regularization can reduce overfitting. Training on a large and diverse training set can also reduce overfitting.¹

Overfitting is like strictly following advice from only your favorite teacher. You’ll probably be successful in that teacher’s class, but you might “overfit” to that teacher’s ideas and be unsuccessful in other classes. Following advice from a mixture of teachers will enable you to adapt better to new situations.¹

See also

• ML crash course - Datasets, generalization, and overfitting

Footnotes

1. developers.google.com/machine-learning/glossary#overfitting ↩ ↩²