An effective heuristic for developing hybrid feature selection in high dimensional and low sample size datasets

An effective heuristic for developing hybrid feature selection in high dimensional and low sample size datasets

Abstract Background High-dimensional datasets with low sample sizes (HDLSS) are pivotal in the fields of biology and bioinformatics. One of core objective of HDLSS is to select most informative features and discarding redundant or irrelevant features. This is particularly crucial in bioinformatics,...

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Bibliographic Details
Main Authors: Hyunseok Shin, Sejong Oh
Format: Article
Language:English
Published: BMC 2024-12-01
Series:BMC Bioinformatics
Subjects:
HDLSS
Feature selection
Machine learning
Filter method
Wrapper method
Online Access:https://doi.org/10.1186/s12859-024-06017-9

Internet

https://doi.org/10.1186/s12859-024-06017-9

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