Weighted Fuzzy Similarity Classifier in the Łukasiewicz-Structure
نویسندگان
چکیده
The aim of this paper is to introduce improvements made to a classifier based on the fuzzy similarity [1]. Improvements are based on the use of generalized Łukasiewicz-structure and weight optimization. We are presenting some new results and a more detailed description of the theoretical background and fixing some terminology compared in to our previous work [2]. 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 semantic information about classification results. We will show that if we choose the power value in appropriate manner in the generalized Łukasiewicz-structure and the optimal weights for different features, we will see significant enhancements in classification results. Key-Words: Łukasiewicz-structure, Fuzzy logic, Fuzzy classifier, Similarity measures, Genetic algorithms
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