Regularization in Neural Networks

A modification to training algorithms which attempts to prevent over- or under-fitting of training data by building in a penalty factor for network complexity (typically by penalizing large weights, which correspond to networks modeling functions of high curvature) (Bishop, 1995).
See also Neural Networks .