Designing non-linear minimax and related discriminants by disjoint tangent configurations applied to RBF networks.

Non-linear classification machines seldom are trained under criteria that are usual and useful for linear discriminants, such as minimax, Fisher’s, and other similar criteria. The reason is the learning difficulties that transformation-trainable machines suffer when applying such criteria. However, the possibility of using non-linear machines whose transformations are pre-designed merits attention.