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Subgroup Discovery with Linguistic Rules.

, , and . Fuzzy Sets and Their Extensions: Representation, Aggregation and Models, volume 220 of Studies in Fuzziness and Soft Computing, Springer, (2008)

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Genetic learning of fuzzy rule-based classification systems cooperating with fuzzy reasoning methods., , and . Int. J. Intell. Syst., 13 (10-11): 1025-1053 (1998)Cost Sensitive and Preprocessing for Classification with Imbalanced Data-sets: Similar Behaviour and Potential Hybridizations., , , and . ICPRAM (2), page 98-107. SciTePress, (2012)Alternative OVA Proposals for Cooperative Competitive RBFN Design in Classification Tasks., , , and . IWANN (1), volume 7902 of Lecture Notes in Computer Science, page 331-338. Springer, (2013)NMEEF-SD: Non-dominated Multiobjective Evolutionary Algorithm for Extracting Fuzzy Rules in Subgroup Discovery., , , and . IEEE Trans. Fuzzy Syst., 18 (5): 958-970 (2010)Tackling Multilabel Imbalance through Label Decoupling and Data Resampling Hybridization., , , and . CoRR, (2018)Revisiting Evolutionary Fuzzy Systems: Taxonomy, applications, new trends and challenges., , , and . Knowl. Based Syst., (2015)Analysis of the impact of using different diversity functions for the subgroup discovery algorithm NMEEF-SD., , , and . GEFS, page 17-23. IEEE, (2011)Choosing the proper autoencoder for feature fusion based on data complexity and classifiers: Analysis, tips and guidelines., , , and . Inf. Fusion, (2020)Web usage mining to improve the design of an e-commerce website: OrOliveSur.com., , , , , and . Expert Syst. Appl., 39 (12): 11243-11249 (2012)A Big Data Approach for the Extraction of Fuzzy Emerging Patterns., , , and . Cogn. Comput., 11 (3): 400-417 (2019)