Copyright
©The Author(s) 2024.
World J Hepatol. Nov 27, 2024; 16(11): 1306-1320
Published online Nov 27, 2024. doi: 10.4254/wjh.v16.i11.1306
Published online Nov 27, 2024. doi: 10.4254/wjh.v16.i11.1306
Figure 2 Identification of biomarkers through machine learning algorithms.
A: Least absolute shrinkage and selection operator coefficients profiles; B: Cross-validation for tuning parameter selection. Variables with non-zero coefficients were excluded; C: When n was 3, the classifier had the minimum error in the support vector machine recursive feature elimination model; D: Interpretation chart of two important evaluation indices; E: Venn diagram showing three biomarkers for cirrhosis.
- Citation: Luo JY, Zheng S, Yang J, Ma C, Ma XY, Wang XX, Fu XN, Mao XZ. Development and validation of biomarkers related to anoikis in liver cirrhosis based on bioinformatics analysis. World J Hepatol 2024; 16(11): 1306-1320
- URL: https://www.wjgnet.com/1948-5182/full/v16/i11/1306.htm
- DOI: https://dx.doi.org/10.4254/wjh.v16.i11.1306