Distributed representation of fuzzy rules and its application to pattern classification
Fuzzy Sets and Systems
A neuro-fuzzy method to learn fuzzy classification rules from data
Fuzzy Sets and Systems - Special issue: application of neuro-fuzzy systems
Three objective genetics-based machine learning for linguisitc rule extraction
Information Sciences: an International Journal - Recent advances in genetic fuzzy systems
Information Sciences: an International Journal - Recent advances in genetic fuzzy systems
Combining GP operators with SA search to evolve fuzzy rule based classifiers
Information Sciences: an International Journal - Recent advances in genetic fuzzy systems
Approximative fuzzy rules approaches for classification with hybrid-GA techniques
Information Sciences: an International Journal - Recent advances in genetic fuzzy systems
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Learning fuzzy classification rules from labeled data
Information Sciences—Informatics and Computer Science: An International Journal - Special issue on recent advances in soft computing
Comparison of Heuristic Criteria for Fuzzy Rule Selection in Classification Problems
Fuzzy Optimization and Decision Making
A weighting function for improving fuzzy classification systems performance
Fuzzy Sets and Systems
Weighting fuzzy classification rules using receiver operating characteristics (ROC) analysis
Information Sciences: an International Journal
Elicitation of fuzzy association rules from positive and negative examples
Fuzzy Sets and Systems
A proposal on reasoning methods in fuzzy rule-based classification systems
International Journal of Approximate Reasoning
Adaptive fuzzy rule-based classification systems
IEEE Transactions on Fuzzy Systems
A fuzzy classifier with ellipsoidal regions
IEEE Transactions on Fuzzy Systems
SLAVE: a genetic learning system based on an iterative approach
IEEE Transactions on Fuzzy Systems
Rule Weight Specification in Fuzzy Rule-Based Classification Systems
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Constructing accurate fuzzy classifiers: A new adaptive method for rule-weight specification
International Journal of Knowledge-based and Intelligent Engineering Systems
An efficient classifier to diagnose of schizophrenia based on the EEG signals
Expert Systems with Applications: An International Journal
A method of learning weighted similarity function to improve the performance of nearest neighbor
Information Sciences: an International Journal
Exploration and exploitation balance management in fuzzy reinforcement learning
Fuzzy Sets and Systems
Cooperative fuzzy rulebase construction based on a novel fuzzy decision tree
IIT'09 Proceedings of the 6th international conference on Innovations in information technology
Hierarchical fuzzy clustering decision tree for classifying recipes of ion implanter
Expert Systems with Applications: An International Journal
Complexity analysis of the biomedical signal using fuzzy entropy measurement
Applied Soft Computing
Diagnosis of cardiac arrhythmia using fuzzy immune approach
ICANNGA'11 Proceedings of the 10th international conference on Adaptive and natural computing algorithms - Volume Part II
Rule weights in a neuro-fuzzy system with a hierarchical domain partition
International Journal of Applied Mathematics and Computer Science
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part II
A hierarchical approach to multi-class fuzzy classifiers
Expert Systems with Applications: An International Journal
Adaptability, interpretability and rule weights in fuzzy rule-based systems
Information Sciences: an International Journal
A new fuzzy rule-based classification system for word sense disambiguation
Intelligent Data Analysis
A fuzzy system index to preserve interpretability in deep tuning of fuzzy rule based classifiers
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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In fuzzy rule-based classification systems (FRBCSs), rule weighting has often been used as a simple mechanism to tune the classifier. In past research, a number of heuristic rule weight specification methods have been proposed for this purpose. A learning algorithm based on reward and punishment has also been proposed to adjust the weights of each fuzzy rule in the rule-base. In this paper, a new method of learning rule weight in FRBCSs is proposed. The method can be used when single winner or weighted vote methods of reasoning is used. Compared with reward and punishment scheme, the proposed method is much faster and more effective. Another advantage of the proposed method is that, during the learning process, redundant rules are removed (i.e., by setting their weights to zero). The final rule-base usually contains much fewer rules than the initial one. This feature is very useful since a compact rule-base is usually desired from the point of efficiency and interpretability. A number of UCI data sets are used to assess the performance of the proposed method in comparison with reward and punishment scheme.