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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Bibliographic Details
Main Author: Freeh N. Alenezi
Format: Article
Language:English
Published: Nature Publishing Group 2021-08-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-021-96389-2