Four Matching Operators of Fuzzy Decision Tree Induction
Linyan Xue, Xiao-hua Zuo, Dongdong Zhou · 2007
Fuzzy decision tree induction is one of the most popular choices for learning and reasoning from feature-based examples. A fuzzy decision tree can be constructed from a training set of cases and converted into a set of fuzzy rules. In this paper, the reasoning ability of four matching operators (or,nland) , (or,times) , (+, nland) and (+,times), which are used for applying fuzzy rules to classification, are analyzed and compared. The purpose of this study is to show some useful guidelines on how to choose an appropriate operator for classified problem.