高维特征集选择模型研究  

Study on the model of feature selection from huge feature sets

作　　者：王练[1] 李云[2] 汪血焰 

机构地区：[1]重庆邮电学院,重庆400065 [2]重庆大学计算机学院,重庆400044 [3]重庆移动通讯公司运维中心,重庆400044

出　　处：《重庆邮电学院学报（自然科学版）》2005年第1期113-116,共4页Journal of Chongqing University of Posts and Telecommunications(Natural Sciences Edition)

摘　　要：特征选择是机器学习和模式识别等领域一个关键问题,而高维特征选择又是当今研究的热点和难点。从高维特征选择的模型出发,详细说明高维特征选择所采用的各种算法类型,并分析了该模型的优劣。Feature selection is a key problem in machine learning and pattern recognition, at the same time, feature selection from huge sets(FSHS) is a hot and difficult subject for researchers to study. In this paper, through the model of FSHS, the authors categorize algorithms about FSHS, and analyze the advantages and disadvantages of the model.

关 键 词：特征选择 高维特征集 模型 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]