ASIA unversity:Item 310904400/4688
English  |  正體中文  |  简体中文  |  Items with full text/Total items : 90451/105768 (86%)
Visitors : 11114967      Online Users : 683
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU 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:

    Title: A parallel concept learning algorithm based upon version space strategy
    Authors: T. P. Hong;S. S. Tseng
    Contributors: Department of Information Science and Applications
    Date: 1994
    Issue Date: 2009-11-30 16:03:07 (UTC+8)
    Publisher: Asia University
    Abstract: Applies the technique of parallel processing to concept learning. A parallel version-space learning algorithm based upon the principle of divide-and-conquer is proposed. Its time complexity is analyzed to be O(k log2n) with n processors, where n is the number of given training instances and k is a coefficient depending on the application domains. For a bounded number of processors in real situations, a modified parallel learning algorithm is then proposed. Experimental results are then performed on a real learning problem, showing that our parallel learning algorithm works, and being quite consistent with the results of theoretical analysis. We conclude that when the number of training instances is large, it is worth learning in parallel because of its faster execution
    Relation: IEEE Transactions on Knowledge and Data Engineering 6(6):857-867
    Appears in Collections:[Department of Applied Informatics and Multimedia] Journal Article

    Files in This Item:

    File Description SizeFormat
    310904400-4688.doc52KbMicrosoft Word312View/Open

    All items in ASIAIR are protected by copyright, with all rights reserved.

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