Maximum Relevancy and Minimum Redundancy Based Ensemble Feature Selection Model for Effective Classification

A. Saravanan; Carlos Felix; Marri Umarani

doi:10.1007/978-981-19-2980-9_11

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Maximum Relevancy and Minimum Redundancy Based Ensemble Feature Selection Model for Effective Classification

A. Saravanan Carlos Felix Marri Umarani

Year: 2022 Lecture notes in electrical engineering Pages: 131-146 Publisher: Springer Science+Business Media

DOI: 10.1007/978-981-19-2980-9_11

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Keywords:

Feature selection Redundancy (engineering) Artificial intelligence Computer science Pattern recognition (psychology) Feature (linguistics) Minimum redundancy feature selection Machine learning Data mining Rank (graph theory) Mathematics

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Topics

Face and Expression Recognition

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Machine Learning and Data Classification

Physical Sciences → Computer Science → Artificial Intelligence

Gene expression and cancer classification

Life Sciences → Biochemistry, Genetics and Molecular Biology → Molecular Biology

Maximum Relevancy and Minimum Redundancy Based Ensemble Feature Selection Model for Effective Classification

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