New method for generation type-2 fuzzy partition for FDT

Authors:
Łukasz Bartczuk;Piotr Dziwiński;Janusz T. Starczewski
Affiliations:
Department of Computer Engineering, Czestochowa University of Technology, Czestochowa, Poland;Department of Computer Engineering, Czestochowa University of Technology, Czestochowa, Poland;Department of Computer Engineering, Czestochowa University of Technology, Czestochowa, Poland and Academy of Management, SWSPiZ, Institute of Information Technology, Łódź, Poland
Venue:
ICAISC'10 Proceedings of the 10th international conference on Artificial intelligence and soft computing: Part I
Year:
2010

Citing 7
Cited 0

C4.5: programs for machine learning

C4.5: programs for machine learning
Pattern Recognition with Fuzzy Objective Function Algorithms

Pattern Recognition with Fuzzy Objective Function Algorithms
Induction of Decision Trees

Machine Learning
Type-2 Fuzzy Decision Trees

ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Fuzzy decision trees: issues and methods

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Interval type-2 fuzzy logic systems: theory and design

IEEE Transactions on Fuzzy Systems
Interval Type-2 Fuzzy Logic Systems Made Simple

IEEE Transactions on Fuzzy Systems

Quantified Score

Hi-index	0.01

Visualization

Abstract

One of the most important tasks during application of fuzzy decision tree algorithms is to generate a fuzzy partition. In this paper, we introduce a new method to perform this task. The proposed method is a two stage process. The second stage is based on the classical Fuzzy C-means (FCM) clustering.