The development of fuzzy decision trees in the framework of Axiomatic Fuzzy Set logic
Applied Soft Computing
A fuzzy decision tree-based duration model for Standard Yorùbá text-to-speech synthesis
Computer Speech and Language
Brain tumor characterization using the soft computing technique of fuzzy cognitive maps
Applied Soft Computing
Fuzzy decision tree based approach to predict the type of pavement repair
AIC'07 Proceedings of the 7th Conference on 7th WSEAS International Conference on Applied Informatics and Communications - Volume 7
WSEAS Transactions on Information Science and Applications
Travel Speed Prediction Using Fuzzy Reasoning
ICIRA '08 Proceedings of the First International Conference on Intelligent Robotics and Applications: Part I
Class Specific Fuzzy Decision Trees for Mining High Speed Data Streams
Fundamenta Informaticae
Data Mining and Knowledge Discovery
GASepo-a software solution for quantitative analysis of digital images in Epo doping control
Computer Methods and Programs in Biomedicine
Human-machine interaction issues in quality control based on online image classification
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A gradient-descent-based approach for transparent linguistic interface generation in fuzzy models
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Optimized fuzzy decision tree using genetic algorithm
ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
Intron identification approaches based on weighted features and fuzzy decision trees
Computers in Biology and Medicine
Class Specific Fuzzy Decision Trees for Mining High Speed Data Streams
Fundamenta Informaticae
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A fuzzy knowledge-based network is developed based on the linguistic rules extracted from a fuzzy decision tree. A scheme for automatic linguistic discretization of continuous attributes, based on quantiles, is formulated. A novel concept for measuring the goodness of a decision tree, in terms of its compactness (size) and efficient performance, is introduced. Linguistic rules are quantitatively evaluated using new indices. The rules are mapped to a fuzzy knowledge-based network, incorporating the frequency of samples and depth of the attributes in the decision tree. New fuzziness measures, in terms of class memberships, are used at the node level of the tree to take care of overlapping classes. The effectiveness of the system, in terms of recognition scores, structure of decision tree, performance of rules, and network size, is extensively demonstrated on three sets of real-life data.