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Random Forest with 200 Selected Features: An Optimal Model for Bioinformatics Research.

, , , and . ICMLA (1), page 154-160. IEEE, (2013)

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Optimizing Wrapper-Based Feature Selection for Use on Bioinformatics Data., , and . FLAIRS, AAAI Press, (2014)Feature list aggregation approaches for ensemble gene selection on patient response datasets., , , and . IRI, page 317-324. IEEE Computer Society, (2013)Using feature selection and classification to build effective and efficient firewalls., , , , , and . IRI, page 850-854. IEEE Computer Society, (2014)How ranker and learner choice affects classification performance on noisy bioinformatics data., , , and . IRI, page 277-282. IEEE Computer Society, (2014)A New Fixed-Overlap Partitioning Algorithm for Determining Stability of Bioinformatics Gene Rankers., , and . ICMLA (2), page 170-177. IEEE, (2012)978-1-4673-4651-1.Vibration analysis for ocean turbine reliability models.. Florida Atlantic University, Boca Raton, USA, (2012)ndltd.org (oai:fau.digital.flvc.org:fau_4056).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)Using Correlation-Based Feature Selection for a Diverse Collection of Bioinformatics Datasets., , and . BIBE, page 156-162. IEEE Computer Society, (2014)Network Traffic Prediction Models for Near- and Long-Term Predictions., , , and . BIBE, page 362-368. IEEE Computer Society, (2014)Feature Selection with High-Dimensional Imbalanced Data., , , and . ICDM Workshops, page 507-514. IEEE Computer Society, (2009)