Screening Nonlinear miRNA Features of Breast Cancer by Using Ensemble Regularized Polynomial Logistic Regression-Reference-Cited by-同舟云学术

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Screening Nonlinear miRNA Features of Breast Cancer by Using Ensemble Regularized Polynomial Logistic Regression

Published:2024-07-01 Issue:7 Volume:31 Page:670-690
ISSN:1557-8666
Container-title:Journal of Computational Biology
language:en
Short-container-title:Journal of Computational Biology

Author:

LI JUNTAO¹²,XIANG SHAN¹²,SONG XUEKUN³

Affiliation:

1. College of Mathematics and Information Science, Henan Normal University, Xinxiang, China.

2. Henan Engineering Laboratory for Big Data Statistical Analysis and Optimal Control, Xinxiang, China.

3. College of Information Technology, Henan University of Chinese Medicine, Zhengzhou, China.

Publisher

Mary Ann Liebert Inc

Link

https://www.liebertpub.com/doi/pdf/10.1089/cmb.2023.0289

Reference53 articles.

1. A penalized quantitative structure–property relationship study on melting point of energetic carbocyclic nitroaromatic compounds using adaptive bridge penalty

2. Regularized logistic regression with adjusted adaptive elastic net for gene selection in high dimensional cancer classification

3. Penalized logistic regression with the adaptive LASSO for gene selection in high-dimensional cancer classification

4. Quantitative structure-activity relationship model for classifying the diverse series of antifungal agents using ratio weighted penalized logistic regression

5. Gene selection and classification of microarray gene expression data based on a new adaptive L1-norm elastic net penalty

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