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Soft Aggregation Methods in Case Based Reasoning
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FR3: a fuzzy rule learner for inducing reliable classifiers
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IFSA'03 Proceedings of the 10th international fuzzy systems association World Congress conference on Fuzzy sets and systems
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Support Vector Machines for Pattern Classification
Scalable Fuzzy Algorithms for Data Management and Analysis: Methods and Design
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Classification with guaranteed probability of error
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IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
In Defense of Fuzzy Association Analysis
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Designing decision trees with the use of fuzzy granulation
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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IEEE Transactions on Fuzzy Systems
On the representation, measurement, and discovery of fuzzy associations
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IEEE Transactions on Fuzzy Systems
Fuzzy rule induction in a set covering framework
IEEE Transactions on Fuzzy Systems
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A possibilistic approach to clustering
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The development of methods for machine learning and data mining has attracted increasing attention in the fuzzy set community in recent years. The aim of this paper is to assess the relevance of fuzzy set theory and fuzzy logic for these fields, highlighting potential contributions without concealing alleged limitations and shortcomings of current research. To this end, some typical applications of fuzzy logic will be reviewed, followed by a more systematic discussion of possible benefits of fuzzy methods. © 2011 John Wiley & Sons, Inc. WIREs Data Mining Knowl Discov 2011 1 269–283 DOI: 10.1002/widm.34