Properties of learning of a Fuzzy ART Variant
Abbreviated Journal Title
neural network; unsupervised learning; supervised learning; clustering; adaptive resonance theory; NEURAL-NETWORK; ARCHITECTURE; RECOGNITION; CLASSIFICATION; PATTERNS; SEARCH; Computer Science, Artificial Intelligence
This paper discusses a variation of the Fuzzy ART algorithm referred to as the Fuzzy ART Variant. The Fuzzy ART Variant is a Fuzzy ART algorithm that uses a very large choice parameter value. Based on the geometrical interpretation of the weights in Fuzzy ART, useful properties of learning associated with the Fuzzy ART Variant are presented and proven. One of these properties establishes an upper bound on the number uf list presentations required by the Fuzzy ART Variant to learn an arbitrary list of input patterns. This bound is small and demonstrates the short-training time property of the Fuzzy ART Variant. Through simulation, it is shown that the Fuzzy ART Variant is as good a clustering algorithm as a Fuzzy ART algorithm that uses typical (i.e. small) values for the choice parameter. (C) 1999 Elsevier Science Ltd. All rights reserved.
"Properties of learning of a Fuzzy ART Variant" (1999). Faculty Bibliography 1990s. 2644.