Feature selection for classification using WGCNA and Spread Sub-Sample for an imbalanced rheumatoid arthritis RNASEQ data

Feature selection for classification using WGCNA and Spread Sub-Sample for an imbalanced rheumatoid arthritis RNASEQ data

An imbalanced classification problem occurs when the distribution of samples among different classes is uneven or biased. Handling small and imbalanced training datasets poses a notable challenge in machine learning, especially in domains such as bioinformatics and medical research. These challenges...

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Bibliographic Details
Main Authors: Consolata Gakii, Victoria Mukami, Boaz Too
Format: Article
Language:English
Published: Elsevier 2023-01-01
Series:Informatics in Medicine Unlocked
Subjects:
Imbalanced data
Rheumatic arthritis
Machine learning
Spread sub-sample
RNASeq
Online Access:http://www.sciencedirect.com/science/article/pii/S2352914823002484

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http://www.sciencedirect.com/science/article/pii/S2352914823002484

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