Medical data set classification using a new feature selection algorithm combined with twin-bounded support vector machine

Márcio Dias de Lima; Juliana de Oliveira Roque e Lima; Rommel Barbosa

doi:10.1007/s11517-019-02100-z

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Medical data set classification using a new feature selection algorithm combined with twin-bounded support vector machine

Márcio Dias de Lima Juliana de Oliveira Roque e Lima Rommel Barbosa

Year: 2020 Journal: Medical & Biological Engineering & Computing Vol: 58 (3)Pages: 519-528 Publisher: Springer Science+Business Media

DOI: 10.1007/s11517-019-02100-z

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Keywords:

Support vector machine Feature selection Robustness (evolution) Computer science Artificial intelligence Machine learning Data mining Data set Benchmark (surveying) Algorithm Feature (linguistics) Statistical classification Bounded function Pattern recognition (psychology) Mathematics

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Face and Expression Recognition

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Text and Document Classification Technologies

Physical Sciences → Computer Science → Artificial Intelligence

Machine Learning and Data Classification

Physical Sciences → Computer Science → Artificial Intelligence

Medical data set classification using a new feature selection algorithm combined with twin-bounded support vector machine

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