Introduction to artificial neural systems
Introduction to artificial neural systems
C4.5: programs for machine learning
C4.5: programs for machine learning
Neuro-fuzzy architectures and hybrid learning
Neuro-fuzzy architectures and hybrid learning
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
Machine Learning
Fuzzy Modeling and Control
A new version of the Fuzzy-ID3 algorithm
ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
Fuzzy decision trees: issues and methods
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Uncertain Fuzzy Clustering: Interval Type-2 Fuzzy Approach to C-Means
IEEE Transactions on Fuzzy Systems
New method for generation type-2 fuzzy partition for FDT
ICAISC'10 Proceedings of the 10th international conference on Artificial intelligence and soft computing: Part I
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This paper presents type-2 fuzzy decision trees (T2FDTs) that employ type-2 fuzzy sets as values of attributes. A modified fuzzy double clustering algorithm is proposed as a method for generating type-2 fuzzy sets. This method allows to create T2FDTs that are easy to interpret and understand. To illustrate performace of the proposed T2FDTs and in order to compare them with results obtained for type-1 fuzzy decision trees (T1FDTs), two benchmark data sets, available on the internet, have been used.