English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 58059/91642 (63%)
造访人次 : 13728118      在线人数 : 62
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜寻范围 查询小技巧:
  • 您可在西文检索词汇前后加上"双引号",以获取较精准的检索结果
  • 若欲以作者姓名搜寻,建议至进阶搜寻限定作者字段,可获得较完整数据
  • 进阶搜寻

    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/75831

    题名: Feature Selection for Cancer Classification on Microarray Expression Data
    作者: Hsu, Hui-huang;Lu, Ming-da
    贡献者: 淡江大學資訊工程學系
    关键词: Cancer Classification;Feature Selection;Microarray;Pearson Correlation Coefficient;Support Vector Machine
    日期: 2008-11
    上传时间: 2012-04-17 22:07:19 (UTC+8)
    出版者: IEEE; International Fuzzy Systems Association; National Kaohsiung University of Applied Sciences
    摘要: Microarray is an important tool in gene analysis research. It can help identify genes that might cause various cancers. In this paper, we use feature selection methods and the support vector machine (SVM) to search for the disease-causing genes in microarray data of three different cancers. The feature selection methods are based on Euclidian distance (ED) and Pearson correlation coefficient(PCC). We investigated the effect on prediction results by training the SVM with different numbers of features and different kinds of kernels. The results show that linear kernel is the fittest kernel for this problem. Also, equal or higher accuracy can be achieved with only 15 to 100 features which are selected from 7129 or more features of the original data sets.
    關聯: Proceedings of the Eighth International Conference on Intelligent Systems Design and Applications (ISDA'08) v.3, pp.153-158
    DOI: 10.1109/ISDA.2008.198
    显示于类别:[資訊工程學系暨研究所] 會議論文


    档案 描述 大小格式浏览次数
    Feature Selection for Cancer Classification on Microarray Expression Data.pdf334KbAdobe PDF543检视/开启



    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回馈