LogSum + L 2 penalized logistic regression model for biomarker selection and cancer classification
Abstract Biomarker selection and cancer classification play an important role in knowledge discovery using genomic data. Successful identification of gene biomarkers and biological pathways can significantly improve the accuracy of diagnosis and help machine learning models have better performance o...
Main Authors: | Xiao-Ying Liu, Sheng-Bing Wu, Wen-Quan Zeng, Zhan-Jiang Yuan, Hong-Bo Xu |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Publishing Group
2020-12-01
|
Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-020-79028-0 |
Similar Items
-
Logsum using Garbled Circuits.
by: José Portêlo, et al.
Published: (2015-01-01) -
Log-logistic Regression and Log-normal Regression Application in the Housing Loans
by: Chih-Ming Tsai, et al.
Published: (2007) -
Coordinate Descent Based Hierarchical Interactive Lasso Penalized Logistic Regression and Its Application to Classification Problems
by: Jin-Jia Wang, et al.
Published: (2014-01-01) -
The Log-gamma-logistic Regression Model: Estimation, Sensibility and Residual Analysis
by: Elizabeth M. Hashimoto, et al.
Published: (2017-11-01) -
The New Odd Log-Logistic Generalized Inverse Gaussian Regression Model
by: Julio Cezar Souza Vasconcelos, et al.
Published: (2019-01-01)