What Is Overfitting?
In quantitative finance, Overfitting is a term used to describe the phenomenon where a model performs well on the data it was trained on, but poorly on new data. This is often caused by the model learning the noise in the data rather than the underlying pattern.
Overfitting can be avoided by using a larger training set, or by using regularization techniques such as dropout or weight decay. It is also important to use cross-validation to ensure that the model is not overfitting to the training data.