Improving the classification accuracy using biomarkers selected from machine learning methods

• 作者: Linduni M.Rodrigo Ashoka D.Polpitiya
• 来源期刊: 控制理论与技术（英文版）
• 年，卷（期）: 2021,（4）
• 所属期刊栏目: Special Issue on Cyber-Physical Systems and Intelligent Control in Honor of the 65th Birthday of Professor Bijoy K. Ghosh
• 页码范围: 538-543
• 页数: 6页
• 语种: 英文

摘要

High-dimensional data encountered in genomic and proteomic studies are often limited by the sample size but has a higher number of predictor variables.Therefore selecting the most relevant variables that are correlated with the outcome variable is a crucial step.This paper describes an approach for selecting a set of optimal variables to achieve a classification model with high predictive accuracy.The work described using a biological classifier published elsewhere but it can be generalized for any application.