English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 64178/96951 (66%)
造訪人次 : 9274967      線上人數 : 13635
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/107156


    題名: Mining Drift of Fuzzy Membership Functions
    作者: Hong, Tzung-Pei;Wu, Min-Thai;Li, Yan-Kang;Chen, Chun-Hao
    關鍵詞: Concept drift;Data mining;Fuzzy C-means;Membership functions
    日期: 2016-03-14
    上傳時間: 2016-08-18 13:32:52 (UTC+8)
    摘要: In this paper, the fuzzy c-means (FCM) clustering approach is adopted to find concept drift of fuzzy membership functions. The proposed algorithm is divided into two stages. In the first stage, the FCM approach is used to find appropriate fuzzy membership functions at different periods or at different places. Then in the second stage, the proposed algorithm compares the results in the first stage to find different types of drift of fuzzy membership functions. Experiments are also made to show the performance of the proposed approach.
    關聯: the series Lecture Notes in Computer Science 9622, pp.211-218
    顯示於類別:[資訊工程學系暨研究所] 會議論文

    文件中的檔案:

    檔案 大小格式瀏覽次數
    index.html0KbHTML179檢視/開啟

    在機構典藏中所有的資料項目都受到原著作權保護.

    TAIR相關文章

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