Fuzzy rule-based systems
نویسنده
چکیده
Relations between similarity-based systems, evaluating similarity to some prototypes, and fuzzy rule-based systems, aggregating values of membership functions, are investigated. Similarity measures based on information theory and probabilistic distance functions lead to a new type of membership functions applicable to symbolic data. Fuzzy membership functions on the other hand lead to a new type of distance functions. Several such novel functions are presented. This approach opens new ways to generate fuzzy rules based either on individual features or on their combinations used to evaluate similarity. Transition from prototype-based rules using similarity and fuzzy rules is illustrated using artificial data in two dimensions. As an illustration of usefulness of prototype-based rules very simple rules are derived for leukemia gene expression data.
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