Improving the classification accuracy using biomarkers selected from machine learning methods
Linduni M.Rodrigo1
Ashoka D.Polpitiya2
1.Department of Mathematics and Statistics,University of Sydney,Sydney,NSW 2006,Australia2.Colombo School of Business and Management,Colombo,Sri Lanka
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.
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论文发表日期：2021-11-05
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：6( 538-543 )
英文信息