Twelve numerical, symbolic and hybrid supervised classification methods

摘要

Supervised classification has already been the subject of numerous studies in the fields of Statistics, Pattern Recognition and Artificial Intelligence under various appel- lations which include discriminant analysis, discrimination and concept learning. Many practical applications relating to this field have been developed. New methods have ap- peared in recent years, due to developments concerning Neural Networks and Machine Learning. These "hybrid" approaches share one common factor in that they combine Symbolic and numerical aspects.