• DocumentCode
    1595408
  • 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
  • fYear
    2010
  • Firstpage
    819
  • Lastpage
    824
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Informatics (INDIN), 2010 8th IEEE International Conference on
  • Conference_Location
    Osaka
  • Print_ISBN
    978-1-4244-7298-7
  • Type

    conf

  • DOI
    10.1109/INDIN.2010.5549638
  • Filename
    5549638