An Efficient Statistical Model Based Classification Algorithm for Classifying Cancer Gene Expression Data with Minimal Gene Subsets

• Published in: International Journal of Cyber Society and Education Vol. 2; no. 2; pp. 051 - 066
• Main Authors: Mallika Rangasamy, Saravanan Venketraman
• Format: Journal Article
• Language: Chinese
• Published: 台灣 Academy of Taiwan Information Systems Research 01.12.2009
• Subjects: ANOVA P-values; Classification; Microarray Data; Prediction; SVM-OAA, LDA

Data mining algorithms are extensively used to classify gene expression data, in which prediction of disease plays a vital role. This paper aims to develop a new classification algorithm for cancer gene expression data using minimal number of gene combinations i.e. minimum gene subsets. The model us...