Decision Tree Based Fuzzy Reasoning
نویسنده
چکیده
Fuzzy logic techniques are efficient in solving complex, ill-defined problems that are characterized by uncertainty of environment and fuzziness of information. Fuzzy logic allows handling uncertain and imprecise knowledge and provides a powerful framework for reasoning. Fuzzy reasoning models are relevant to a wide variety of subject areas such as engineering, economics, psychology, sociology, finance, and education. For most of these applications, fuzzy system or hybrid fuzzy system is developed to deal with complex data. This paper presents a new hybrid fuzzy system model which is named as decision tree based fuzzy expert model (DFEM). Decision tree learning is used to extract patterns from dataset and the extracted patterns are used in terms of rules in the fuzzy rule base. The proposed model is tested on a car evaluation dataset and it shows best results. Decision tree learning; fuzzy logic (keywords)
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