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...
Main Authors: | Nashwan Alromema, Asif Hassan Syed, Tabrej Khan |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-02-01
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Series: | Diagnostics |
Subjects: | |
Online Access: | https://www.mdpi.com/2075-4418/13/4/708 |
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