This paper describes eecient methods for exact and approximate implementation of the MIN-FEATURES bias, which prefers consistent hypotheses deenable over as few features as possible. This bias is useful for learning domains where many irrelevant features are present in the training data. We rst introduce FOCUS-2, a new algorithm that exactly implements the MIN-FEATURES bias. This algorithm is e...

Active contours, very popular in image segmentation, suffer from delicate adjustments of many parameters. We propose to carry out these adjustments using genetic algorithm. Here an active contour is implemented using a greedy algorithm. Within this framework, two approaches are presented. A supervised approach which delivers a global set of parameters. In this case the greedy algorithm is invol...