English  |  正體中文  |  简体中文  |  Items with full text/Total items : 56829/90592 (63%)
Visitors : 12149577      Online Users : 65
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/90308

    Title: 基於類-屬性關聯度的啟發式離散化技術
    Other Titles: Heuristic discretization technique based on the class-attribute interdependence
    Authors: 周世昊;倪衍森
    Contributors: 淡江大學管理科學學系
    Keywords: 離散化;數據挖掘;自頂向下;變精度粗糙集;不一致;discretization;data mining;top-down;variable precision rough sets;inconsistency
    Date: 2011-10
    Issue Date: 2013-06-10 16:25:30 (UTC+8)
    Publisher: 瀋陽市:東北大學
    Abstract: Discretization algorithms play an important role in many areas such as data mining, machine learning and artificial intelligence. Therefore, a heuristic discretization technique based on the class-attribute interdependence is proposed. A new discretization criterion is defined, which selects best cut points in terms of characteristics of the data itself and overcomes the existing deficiencies of state-of-the-art top-down discretization methods. A novel measure of inconsistency based on variable precision rough sets(VPRS) model is developed, which effectively controls information loss generated by discretization and allows an adaptive degree of misclassification. Empirical experiments and statistical analysis show that the proposed technique generates a better discretization scheme which significantly improves the accuracy of classification by running J4.8 and SVM.
    Relation: 控制與決策=Control and Decision 26(10),頁1504-1510
    Appears in Collections:[Department of Management Sciences] Journal Article

    Files in This Item:

    File Description SizeFormat

    All items in 機構典藏 are protected by copyright, with all rights reserved.

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