Evaluation of The Fuzzy Decision Tree for Investigation of Kansei Information

Abstract

In this paper, we propose a method for investigation of Kansei information with Fuzzy C4.5 decision tree. In the case of Kansei information investigation, finding rules from constructed decision tree is required to be simple and easy to be understood. In our previous research, we had investigated the change of structure of constructed Fuzzy C4.5 decision tree from various types of membership functions and parameters for pruning. We found some optimized decision trees and rules about usability of golf clubs, which was an example for Kansei information investigation. In this paper, we evaluate stability of constructed Fuzzy C4.5 decision tree. We also compare the estimation abilities of fuzzy C4.5 decision tree with standard C4.5 decision tree.