The Effective Number of Parameters: An Analysis of Generalization and Regularization in Nonlinear Learning Systems
–Neural Information Processing Systems
We present an analysis of how the generalization performance (expected test set error) relates to the expected training set error for nonlinear learning systems,such as multilayer perceptrons and radial basis functions.
Neural Information Processing Systems
Dec-31-1992