Majority scoring with backward elimination in PLS for high dimensional spectrum data

Abstract Variable selection is crucial issue for high dimensional data modeling, where sample size is smaller compared to number of variables. Recently, majority scoring of filter measures in PLS (MS-PLS) is introduced for variable selection in high dimensional data. Filter measures are not greedy f...

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Autor principal: Freeh N. Alenezi
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/dc55cfc4d44f4cbdb4a9bee95682efe4
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