Ensemble feature selection in high dimension, low sample size datasets: Parallel and serial combination approaches

Chih‐Fong Tsai; Ya-Ting Sung

doi:10.1016/j.knosys.2020.106097

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Ensemble feature selection in high dimension, low sample size datasets: Parallel and serial combination approaches

Chih‐Fong Tsai Ya-Ting Sung

Year: 2020 Journal: Knowledge-Based Systems Vol: 203 Pages: 106097-106097 Publisher: Elsevier BV

DOI: 10.1016/j.knosys.2020.106097

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Keywords:

Feature selection Computer science Pattern recognition (psychology) Feature (linguistics) Selection (genetic algorithm) Artificial intelligence Dimensionality reduction sort Ensemble learning Minimum redundancy feature selection Data mining Machine learning

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Gene expression and cancer classification

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

Face and Expression Recognition

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Neural Networks and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Ensemble feature selection in high dimension, low sample size datasets: Parallel and serial combination approaches

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