Fuzzy variable-branch decision tree

Shiueng-Bien Yang

doi:10.1117/1.3504357

1 October 2010 Fuzzy variable-branch decision tree

Shiueng-Bien Yang

Author Affiliations +

Journal of Electronic Imaging, Vol. 19, Issue 4, 043012 (October 2010). https://doi.org/10.1117/1.3504357

Abstract

Decision trees and their variants recently have been proposed. All trees used are fixed M-ary tree structured, such that the training samples in each node must be artificially divided into a fixed number of branches. This work proposes a fuzzy variable-branch decision tree (FVBDT) based on the fuzzy genetic algorithm (FGA). The FGA automatically searches for the proper number of branches of each node according to the classification error rate and the classification time of FVBDT. Therefore, FGA reduces both the classification error rate and classification time, and then optimizes the FVBDT. In our experiments, FVBDT outperforms the traditional C-fuzzy decision tree (CFDT) based on the fuzzy C-means (FCM) algorithm.

©(2010) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Shiueng-Bien Yang "Fuzzy variable-branch decision tree," Journal of Electronic Imaging 19(4), 043012 (1 October 2010). https://doi.org/10.1117/1.3504357

Published: 1 October 2010

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