Learning curve

Also written: learning curves

A chart of training and validation scores as the training set grows. The gap between the lines shows whether more data would help.

Other terms from the same lesson

• bias-variance tradeoff: Simple models miss in a steady way (bias); flexible models swing with every change in the data (variance). The best model balances the two.
• double descent: When a model is made far bigger than the data seems to justify, its test error can fall again after first rising. It's one reason huge neural networks still generalize.