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...
Main Author: | |
---|---|
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 |