Title :
Cancer molecular classification based on support vector machines
Author :
Li, Yingxin ; Liu, Quanjin ; Ruan, Xiaogang
Author_Institution :
Sch. of Electron. Information & Control Eng., Beijing Univ. of Technol., China
Abstract :
A method based on support vector machines is proposed for cancer molecular classification. The Bhattacharyya distance of each gene is calculated as the criterion for filtering ´noisy-genes´ which do not contribute to classification, and then based on the expression values of the informative genes, a linear support vector machine is used as the classifier to classify different cancers. This process has been applied to the human acute leukemia dataset as a test case. The effectiveness and feasibility of the method is proved by the results that all the samples in the dataset can be correctly classified without any error.
Keywords :
cancer; medical image processing; molecular biophysics; pattern classification; Bhattacharyya distance; cancer molecular classification; gene expression profile; human acute leukemia dataset; noisy-genes filtering; support vector machines; Cancer; Control engineering; Educational institutions; Electronic mail; Filtering; Humans; Nonlinear filters; Support vector machine classification; Support vector machines; Testing;
Conference_Titel :
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN :
0-7803-8273-0
DOI :
10.1109/WCICA.2004.1343789
