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一种自适应的Tri-Training半监督算法
引用本文:彭雅琴,宫宁生.一种自适应的Tri-Training半监督算法[J].计算机系统应用,2016,25(8):130-134.
作者姓名:彭雅琴  宫宁生
作者单位:三江学院 计算机科学与工程学院, 南京 210012,南京工业大学 计算机科学与工程学院, 南京 210009
摘    要:Tri-Training算法是半监督算法的一种,在学习过程中容易错误标注无标记样本,从而降低分类性能,为此提出一种ADP-Tri-Training(Adaptive Tri-Training)算法,改进协同工作方式,根据几何中心设置分类器组成,然后应用模糊数学理论将多个独立的分类器组合,使得算法可以在多因素下综合评价样本,并在此基础上引入遗传算法动态设置组合权重以适应于具体的样本集,从而尽可能降低样本标注的错误率,多个实验结果表明ADP-Tri-Training算法具有更好的分类性能.

关 键 词:Tri-Training算法  自适应  遗传算法  差异性度量  半监督
收稿时间:2015/11/30 0:00:00
修稿时间:2016/1/18 0:00:00

Adaptive Tri-Training Semi-Supervised Algorithm
PENG Ya-Qin and GONG Ning-Sheng.Adaptive Tri-Training Semi-Supervised Algorithm[J].Computer Systems& Applications,2016,25(8):130-134.
Authors:PENG Ya-Qin and GONG Ning-Sheng
Affiliation:Department of Computer Science and Engineering, Sanjiang University, Nanjing 210012, China and Department of Computer Science and Engineering, Nanjing University of Technology, Nanjing 210009, China
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.
Keywords:Tri-Training algorithm  adaptive  genetic algorithm  novel diversity measure  semi-supervised
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