Improving Simplified Fuzzy ARTMAP Performance Using Genetic Algorithm for Brain Fingerprint Classification

A genetic algorithm is proposed for ordering the input patterns during training for Simplified Fuzzy ARTMAP (SFA) classifier to improve the individual identification classification performance using brain fingerprints. The results indicate improved classification performance as compared to the existing methods for pattern ordering, namely voting strategy and min-max. As the ordering method is general, it could be used with any dataset to obtain improved classification performance when SFA is used.