Supervised feature selection based on the law of total variance

Supervised feature selection based on the law of total variance

Feature selection is a fundamental pre-processing step in machine learning that decreases data dimensionality by removing superfluous and irrelevant features. This study proposes a supervised feature selection method based on feature relevance by employing the law of total variance (LTV). Specifical...

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Bibliographic Details
Main Authors: Nur Atiqah, Mustapa, Azlyna, Senawi, Wei, Hua-Liang
Format: Article
Language:English
Published: Penerbit UMP 2023
Subjects:
QA Mathematics
Online Access:http://umpir.ump.edu.my/id/eprint/40090/
http://umpir.ump.edu.my/id/eprint/40090/1/Supervised%20Feature%20Selection%20based%20on%20the%20Law%20of%20Total%20Variance.pdf

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