Classifier Based on Maximal Fuzzy Similarity in Łukasiewicz Structure
نویسندگان
چکیده
The aim of this paper is to introduce improvements made to a new type of classifier based on maximal fuzzy similarity [1]. Improvements are based on the use of generalized Łukasiewicz-structures and weight optimization. The main benefits of the classifier are its computational efficiency and its strong mathematical background. It is based on many-valued logic and it provides semantical information about classification problems. Here we will show that if we choose the power value in a right manner in Łukasiewiczstructure and optimal weights, we will see significant enhancements in classification results. 1. CLASSIFICATION BASED ON FUZZY SIMILARITY
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