A causality-inspired feature selection method for cancer imbalanced high-dimensional data
Yijun Liu, Qiang Huang, Huiyan Sun, Yi Chang
This paper introduces a causality-inspired feature selection method, CLAND, to improve accuracy and stability in cancer biomarker discovery from imbalanced omics data.
bioRxiv · Oct 4, 2021 · PreprintBioinformatics