Adaptive hypergraph regularized logistic regression model for bioinformatic selection and classification

Yong Jin; Haipeng Hou; Mian Qin; Wei Yang; Zhen Zhang

doi:10.1007/s10489-024-05304-5

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Adaptive hypergraph regularized logistic regression model for bioinformatic selection and classification

Yong Jin Haipeng Hou Mian Qin Wei Yang Zhen Zhang

Year: 2024 Journal: Applied Intelligence Vol: 54 (3)Pages: 2349-2360 Publisher: Springer Science+Business Media

DOI: 10.1007/s10489-024-05304-5

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Keywords:

Interpretability Computer science Hypergraph Coordinate descent Gene selection Machine learning Data mining Artificial intelligence Selection (genetic algorithm) Gene Microarray analysis techniques Mathematics Biology

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Gene expression and cancer classification

Life Sciences → Biochemistry, Genetics and Molecular Biology → Molecular Biology

Bioinformatics and Genomic Networks

Life Sciences → Biochemistry, Genetics and Molecular Biology → Molecular Biology

Gene Regulatory Network Analysis

Life Sciences → Biochemistry, Genetics and Molecular Biology → Molecular Biology

Adaptive hypergraph regularized logistic regression model for bioinformatic selection and classification

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