overfit

1. (statistics) To use a statistical model that has too many parameters relative to the size of the sample, leading to a good fit with the sample data but a poor fit with new data.Examples: "In all modeling techniques, and neural networks in particular, care must be taken not to overtrain or overfit the model. If possible, models should be interpreted in terms of their mechanistic meaning."; "If your strategy is to always fit and use the global model, you will probably overfit the model (i.e., include unnecessary variables)."Antonyms: underfit