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Evaluation of Wrapper-Based Feature Selection Using Hard, Moderate, and Easy Bioinformatics Data.

, , and . BIBE, page 149-155. IEEE Computer Society, (2014)

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Impact of Noise and Data Sampling on Stability of Feature Selection., , and . ICMLA (1), page 172-177. IEEE Computer Society, (2011)Comparison of approaches to alleviate problems with high-dimensional and class-imbalanced data., , , and . IRI, page 234-239. IEEE Systems, Man, and Cybernetics Society, (2011)Comparative Analysis on the Stability of Feature Selection Techniques Using Three Frameworks on Biological Datasets., , , and . ICMLA (1), page 418-423. IEEE, (2013)Is Gene Selection Enough for Imbalanced Bioinformatics Data?, and . IRI, page 346-355. IEEE, (2018)Comparison of Two Frameworks for Measuring the Stability of Gene-Selection Techniques on Noisy Class-Imbalanced Data., , and . ICTAI, page 881-888. IEEE Computer Society, (2013)How ranker and learner choice affects classification performance on noisy bioinformatics data., , , and . IRI, page 277-282. IEEE Computer Society, (2014)Analysis of machine learning algorithms on bioinformatics data of varying quality.. Florida Atlantic University, Boca Raton, FL, USA, (2015)ndltd.org (oai:fau.digital.flvc.org:fau_31342).The effect of noise level and distribution on classification of easy gene microarray data., , and . IRI, page 297-302. IEEE Computer Society, (2014)Robustness of Threshold-Based Feature Rankers with Data Sampling on Noisy and Imbalanced Data., , and . FLAIRS, AAAI Press, (2012)Filter-Based Subset Selection for Easy, Moderate, and Hard Bioinformatics Data., and . IRI, page 372-377. IEEE, (2018)