Title :
Leukemia cancer classification based on Support Vector Machine
Author :
Hsieh, Sung-Huai ; Wang, Zhenyu ; Cheng, Po-Hsun ; Lee, I-Shun ; Hsieh, Sheau-Ling ; Lai, Feipei
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Providence Univ., Taichung, Taiwan
Abstract :
In the paper, we classify cancer with the Leukemia cancer of medical diagnostic data. Information gain has been adapted for feature selections. A Leukemia cancer model that utilizes Information Gain based on Support Vector Machines (IG-SVM) techniques and enhancements to evaluate, interpret the cancer classification. The experimental results indicate that the SVM model illustrates the highest accuracy of classifications for Leukemia cancer.
Keywords :
cancer; feature extraction; medical diagnostic computing; pattern classification; support vector machines; Leukemia cancer classification; feature selection; information gain; medical diagnostic data; support vector machine technique; Biomedical computing; Biomedical engineering; Cancer; Computer science; Data engineering; Entropy; Gene expression; Machine learning; Support vector machine classification; Support vector machines; Leukemia cancer; microarray; support vector machine;
Conference_Titel :
Industrial Informatics (INDIN), 2010 8th IEEE International Conference on
Conference_Location :
Osaka
Print_ISBN :
978-1-4244-7298-7
DOI :
10.1109/INDIN.2010.5549638
