Adaptive Tri-Training Semi-Supervised Algorithm
CSTR:
Author:
Affiliation:

Clc Number:

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Tri-Training algorithm belongs to semi-supervised algorithm,unlabeled samples are often labeled incorrectly in study, and the performance is affected. So the ADP-Tri-Training (Adaptive Tri-Training) algorithm is proposed, cooperative work mode is improved, a classification composition scheme based on geometric center is used, the fuzzy mathematics theory is applied to combine the classifiers, so the algorithm can evaluate the samples by multiple factors, genetic algorithm is introduced to dynamically set the combined weight in order to adapt different sample sets, also it can reduce the error of classifies as far as possible, finally the experimental results show that the proposed algorithm is more effective.

    Reference
    Related
    Cited by
Get Citation

彭雅琴,宫宁生.一种自适应的Tri-Training半监督算法.计算机系统应用,2016,25(8):130-134

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:November 30,2015
  • Revised:January 18,2016
  • Adopted:
  • Online: August 16,2016
  • Published:
Article QR Code
You are the firstVisitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-3
Address:4# South Fourth Street, Zhongguancun,Haidian, Beijing,Postal Code:100190
Phone:010-62661041 Fax: Email:csa (a) iscas.ac.cn
Technical Support:Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063