Hybrid Computational Intelligence Schemes in Complex Domains: An Extended Review
SETN '02 Proceedings of the Second Hellenic Conference on AI: Methods and Applications of Artificial Intelligence
The development of fuzzy decision trees in the framework of Axiomatic Fuzzy Set logic
Applied Soft Computing
Learning fuzzy rules from fuzzy samples based on rough set technique
Information Sciences: an International Journal
An experimental evaluation of ensemble methods for EEG signal classification
Pattern Recognition Letters
Adaptive Fuzzy Association Rule mining for effective decision support in biomedical applications
International Journal of Data Mining and Bioinformatics
Software Defect Classification: A Comparative Study with Rough Hybrid Approaches
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
A Rough-Hybrid Approach to Software Defect Classification
RSFDGrC '07 Proceedings of the 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
Improving generalization of fuzzy IF-THEN rules by maximizing fuzzy entropy
IEEE Transactions on Fuzzy Systems
A gradient-descent-based approach for transparent linguistic interface generation in fuzzy models
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Prediction and query evaluation using linguistic decision trees
Applied Soft Computing
Optimized fuzzy decision tree using genetic algorithm
ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
Fuzzy ID3 algorithm based on generating Hartley measure
WISM'11 Proceedings of the 2011 international conference on Web information systems and mining - Volume Part II
Induced states in a decision tree constructed by Q-learning
Information Sciences: an International Journal
Extraction of fuzzy rules from fuzzy decision trees: An axiomatic fuzzy sets (AFS) approach
Data & Knowledge Engineering
A hierarchical approach to multi-class fuzzy classifiers
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
An improved algorithm for calculating fuzzy attribute reducts
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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Fuzzy decision tree induction is an important way of learning from examples with fuzzy representation. Since the construction of optimal fuzzy decision tree is NP-hard, the research on heuristic algorithms is necessary. In this paper, three heuristic algorithms for generating fuzzy decision trees are analyzed and compared. One of them is proposed by the authors. The comparisons are twofold. One is the analytic comparison based on expanded attribute selection and reasoning mechanism; the other is the experimental comparison based on the size of generated trees and learning accuracy. The purpose of this study is to explore comparative strengths and weaknesses of the three heuristics and to show some useful guidelines on how to choose an appropriate heuristic for a particular problem