摘要
研究利用Ｔａｂｕ搜索从大特征集中选择一组有效特征的问题．分析了Ｔａｂｕ搜索中表长、邻域大小和候选解数量等参数对Ｔａｂｕ搜索的影响．对两种特征选择的问题，与经典及最近新提出的一些特征选择方法如ＳＦＳ，ＳＢＳ，ＧＳＦＳ，ＧＳＢＳ，ＰＴＡ，ＢＢ，ＧＡ和ＳＦＦＳ，ＳＦＢＳ等算法的实验比较表明，Ｔａｂｕ搜索在求解时间和解的质量上都取得了满意的结果．
In this paper,an algorithm based on tabu search for selecting an optimal subset from original large scale feature set is presented.The role and effect of the parameters in tabu search,such as the tabu list length,the neighbor size and the number of candidate solutions are analyzed.For two forms of feature selection problem,tabu search is compared with classic algorithms,such as sequential and generalized sequential methods,branch and bound methods,plus l and take away r method,etc.,and other methods proposed recently,such as genetic algorithm and sequential floating forward(backward) search methods.The experimental results have shown that tabu search has good performance in both the quality of obtained feature subset and computation efficiency.
出处
《自动化学报》
EI
CSCD
北大核心
1999年第4期457-466,共10页
Acta Automatica Sinica
基金
国家自然科学基金
北京市自然科学基金
关键词
特征选择
TABU搜索
模式分类器
NP问题
Feature selection,tabu search,pattern classifier,search methods,dimension curse.
