Thumbnail
Access Restriction
Subscribed

Author Sung-Huai Hsieh ♦ Zhenyu Wang ♦ Po-Hsun Cheng ♦ I-Shun Lee ♦ Sheau-Ling Hsieh ♦ Feipei Lai
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2010
Language English
Subject Domain (in DDC) Technology ♦ Engineering & allied operations ♦ Applied physics
Subject Keyword Data engineering ♦ Biomedical computing ♦ Entropy ♦ Gene expression ♦ Support vector machines ♦ Computer science ♦ microarray ♦ support vector machine ♦ Support vector machine classification ♦ Machine learning ♦ Leukemia cancer ♦ Cancer ♦ Biomedical engineering
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 cnacer model that utilizes Information Gain based on Support Vector Machines (IG-SVM) techniques and enhancements to evaluate, interpret the cacer classification. The experimental results indicate that the SVM model illustrates the highest accuracy of classifications for Leukemia cancer.
Description Author affiliation: Department of Computer Science and Information Engineering, Providence University, Taiwan (Sung-Huai Hsieh) || Network and Computer Centre, National Chiao Tung University, Hsin Chu, Taiwan (I-Shun Lee; Sheau-Ling Hsieh) || Computing Laboratory, Oxford University, UK (Zhenyu Wang) || Department of Software Engineering, National Kaohsiung Normal University, Taiwan (Po-Hsun Cheng) || Department of Computer Science and Information Engineering National Taiwan University, Taiwan (Feipei Lai)
ISBN 9781424472987
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2010-07-13
Publisher Place Japan
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
e-ISBN 9781424473007
Size (in Bytes) 337.97 kB
Page Count 6
Starting Page 819
Ending Page 824


Source: IEEE Xplore Digital Library