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Enhancing Incremental Feature Subset Selection in High-Dimensional Databases by Adding a Backward Step.

, , , и . ISCIS, стр. 93-97. Springer, (2011)

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Antonio Juan Gámez López

Alberto Eduardo Gámez

Gustavo Adolfo Gámez Armas

Humberto Jorge José

Gerardo Gamez-Corrales

 

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Applicability of Estimation of Distribution Algorithms to the Fuzzy Rule Learning Problem: A Preliminary Study., и . ICEIS, стр. 350-357. (2002)Improving Incremental Wrapper-Based Subset Selection via Replacement and Early Stopping., , и . IJPRAI, 25 (5): 605-625 (2011)Improving the performance of Naive Bayes multinomial in e-mail foldering by introducing distribution-based balance of datasets., , и . Expert Syst. Appl., 38 (3): 2072-2080 (2011)Learning Bayesian Classifiers from Dependency Network Classifiers., , и . ICANNGA (1), том 4431 из Lecture Notes in Computer Science, стр. 806-813. Springer, (2007)Incremental Compilation of Bayesian networks, , и . CoRR, (2012)Learning cooperative linguistic fuzzy rules using fast local search algorithms., , и . FUZZ-IEEE, стр. 1-8. IEEE, (2010)Improving Incremental Wrapper-Based Feature Subset Selection by Using Re-ranking., , и . IEA/AIE (1), том 6096 из Lecture Notes in Computer Science, стр. 580-589. Springer, (2010)A Metahierarchical Rule Decision System to Design Robust Fuzzy Classifiers Based on Data Complexity., , , и . IEEE Trans. Fuzzy Syst., 27 (4): 701-715 (2019)Constrained Score+(Local)Search Methods for Learning Bayesian Networks., и . ECSQARU, том 3571 из Lecture Notes in Computer Science, стр. 161-173. Springer, (2005)Machine learning from crowds: A systematic review of its applications., , и . WIREs Data Mining Knowl. Discov., (2019)