A Hybrid Machine Learning Approach to Screen Optimal Predictors for the Classification of Primary Breast Tumors from Gene Expression Microarray Data

A Hybrid Machine Learning Approach to Screen Optimal Predictors for the Classification of Primary Breast Tumors from Gene Expression Microarray Data

The high dimensionality and sparsity of the microarray gene expression data make it challenging to analyze and screen the optimal subset of genes as predictors of breast cancer (BC). The authors in the present study propose a novel hybrid Feature Selection (FS) sequential framework involving minimum...

Full description

Bibliographic Details
Main Authors: Nashwan Alromema, Asif Hassan Syed, Tabrej Khan
Format: Article
Language:English
Published: MDPI AG 2023-02-01
Series:Diagnostics
Subjects:
primary breast tumor
gene-biomarkers
hybrid-feature selection approach
filter-based fs
two-tailed unpaired <i>t</i>-test
meta-heuristics techniques
Online Access:https://www.mdpi.com/2075-4418/13/4/708

Internet

https://www.mdpi.com/2075-4418/13/4/708

Similar Items