Feature Selection Algorithm for Improving the Performance of Classification: A Survey

被引:8
作者
Naidu, Kajal [1 ]
Dhenge, Aparna [1 ]
Wankhade, Kapil [1 ]
机构
[1] GHRCE Nagpur, Dept IT, Nagpur, Maharashtra, India
来源
2014 FOURTH INTERNATIONAL CONFERENCE ON COMMUNICATION SYSTEMS AND NETWORK TECHNOLOGIES (CSNT) | 2014年
关键词
Data mining; feature selection; genetic algorithm; MUTUAL INFORMATION; RELEVANCE;
D O I
10.1109/CSNT.2014.99
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
With the rapid development of the Computer Science and Technology, It has become a major problem for the users that how to quickly find useful or needed information. Data mining can be seen as an area of artificial intelligence that seeks to extract information or patterns from large amounts of data stored in databases. Recent researches on feature selection have been conducted in an attempt to find efficient methods for selection of relevant features. Feature selection generally involves a combination of search and attributes utility estimation plus evaluation with respect to specific learning schemes. There are several methods to select features in ensembles systems and genetic algorithms (GA) are one of the most used methods. This paper gives overview of feature selection Algorithm which searches the feature space using the idea of evolutionary computation, in order to find the optimal feature subset.
引用
收藏
页码:468 / 471
页数:4
相关论文
共 23 条
[1]  
[Anonymous], 1997, ICML
[2]   Feature selection via coalitional game theory [J].
Cohen, Shay ;
Dror, Gideon ;
Ruppin, Eytan .
NEURAL COMPUTATION, 2007, 19 (07) :1939-1961
[3]  
de L Vieira Davi C., 2010, 2010 IEEE International Conference on Systems, Man and Cybernetics (SMC 2010), P1863, DOI 10.1109/ICSMC.2010.5642280
[4]  
Gao Like, 2005, IEEE INT C DAT MIN
[5]  
Guyon I., 2003, J MACH LEARN RES, V3, P1157
[6]   Benchmarking attribute selection techniques for discrete class data mining [J].
Hall, MA ;
Holmes, G .
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2003, 15 (06) :1437-1447
[7]  
Jihong Liu, 2008, 2008 International Conference on Neural Networks and Signal Processing, P445, DOI 10.1109/ICNNSP.2008.4590390
[8]   Fair attribution of functional contribution in artificial and biological networks [J].
Keinan, A ;
Sandbank, B ;
Hilgetag, CC ;
Meilijson, I ;
Ruppin, E .
NEURAL COMPUTATION, 2004, 16 (09) :1887-1915
[9]   Wrappers for feature subset selection [J].
Kohavi, R ;
John, GH .
ARTIFICIAL INTELLIGENCE, 1997, 97 (1-2) :273-324
[10]   Input feature selection by mutual information based on Parzen window [J].
Kwak, N ;
Choi, CH .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2002, 24 (12) :1667-1671