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benchmarking relief-based feature selection method

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Benchmarking relief-based feature selection methods for bioinformatics data mining

#artificialintelligenceSep-1-2018

Relief-based feature selection (RBAs) efficiently detect feature interactions. RBAs handle genetic heterogeneity, missing/imbalanced data, and quantitative traits. SURF∗ and MultiSURF∗ are not suited to detecting main effects. The new MultiSURF algorithm performs most consistently over different problems. ReBATE software offers easy access to multiple, flexible RBAs.

benchmarking relief-based feature selection method, feature selection method, selection method, (4 more...)

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Industry: Health & Medicine > Pharmaceuticals & Biotechnology (0.38)

Technology: Information Technology > Artificial Intelligence > Machine Learning (1.00)

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