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Improving Fuzzy Rule-Based Decision Models by Means of a Genetic 2-Tuples Based Tuning and the Rule Selection.

, , , , and . MDAI, volume 3885 of Lecture Notes in Computer Science, page 317-328. Springer, (2006)

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A Double Axis Classification of Interpretability Measures for Linguistic Fuzzy Rule-Based Systems., , and . WILF, volume 6857 of Lecture Notes in Computer Science, page 99-106. Springer, (2011)Hybrid learning models to get the interpretability-accuracy trade-off in fuzzy modeling., , , , and . Soft Comput., 10 (9): 717-734 (2006)Obtaining accurate TSK Fuzzy Rule-Based Systems by Multi-Objective Evolutionary Learning in high-dimensional regression problems., , , and . FUZZ-IEEE, page 1-7. IEEE, (2013)Genetic tuning on fuzzy systems based on the linguistic 2-tuples representation., and . FUZZ-IEEE, page 233-238. IEEE, (2004)A case study on the application of instance selection techniques for Genetic Fuzzy Rule-Based Classifiers., , , , and . FUZZ-IEEE, page 1-8. IEEE, (2012)Temporal association rule mining: An overview considering the time variable as an integral or implied component., , , and . WIREs Data Mining Knowl. Discov., (2020)Evolutionary data mining and applications: A revision on the most cited papers from the last 10 years (2007-2017)., , and . WIREs Data Mining Knowl. Discov., (2018)On the Usefulness of MOEAs for Getting Compact FRBSs Under Parameter Tuning and Rule Selection., , , and . Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases, volume 98 of Studies in Computational Intelligence, Springer, (2008)A Multiobjective Evolutionary Algorithm for Tuning Fuzzy Rule Based Systems with Measures for Preserving Interpretability., , and . IFSA/EUSFLAT Conf., page 1146-1151. (2009)A multi-objective evolutionary method for learning granularities based on fuzzy discretization to improve the accuracy-complexity trade-off of fuzzy rule-based classification systems: D-MOFARC algorithm., , and . Appl. Soft Comput., (2014)