An Incremental Fuzzy Rule-based Classification System

• Main Authors: Shih-Hsi Fu, 傅仕熙
• Other Authors: Yee-Tsong Juan
• Format: Others
• Language: zh-TW
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/35c54n

碩士 === 中原大學 === 資訊工程研究所 === 91 === In this paper, we propose an incremental fuzzy rule-based classification system. The main objective is to generate an on-line, dynamic, incremental classification system. A method for automatic construction of an incremental fuzzy rule-based classification system from numerical data using the Simple Fuzzy Grid Method and the information gain of the Classification and Regression Tree (CART) is presented. The Simple Fuzzy Grid Method is developed for an initial fuzzy rule-based classification system from training patterns. When incremental data input, exploiting certainty factor of each fuzzy if-then rule determines whether fuzzy if-then rule need to be repartitioned or not. And the information gain of CART decides how to repartition fuzzy if-then rule. In order to reduce the number of fuzzy if-then rules and to make each fuzzy if-then rule more general, we consider combining two adjacent fuzzy if-then rules. Finally we use Iris and glass database to estimate learning ability, generalization ability and the number of fuzzy if-then rules of the incremental fuzzy rule-based classification system before and after combining. And we compare above characteristics with other fuzzy classification systems. Keyword：Fuzzy Rule-based Classification System, Incremental Learning, Decision Tree, Information Theory