DocumentCode :
2851265
Title :
A Class-Based Feature Selection Method for Ensemble Systems
Author :
Vale, Karliane M O ; Dias, Filipe G. ; Canuto, Anne M P ; Souto, Marcílio C P
Author_Institution :
Inf. & Appl. Math. Dept., Fed. Univ. of RN Natal, Natal
fYear :
2008
fDate :
10-12 Sept. 2008
Firstpage :
596
Lastpage :
601
Abstract :
Diversity is considered as one of the main prerequisites for an efficient use of ensemble systems. One way of increasing diversity is through the use of feature selection methods in ensemble systems. In this paper, a class-based feature selection method for ensemble systems is proposed. The proposed method is inserted into the filter approach of feature selection methods and it chooses only the attributes that are important only for a specific class. An analysis of the performance of the proposed method is also investigated in this paper and it shows that the proposed method has outperformed the standard feature selection method.
Keywords :
pattern recognition; class-based feature selection method; ensemble systems; feature selection method filter approach; pattern recognition; Diversity reception; Filters; Hybrid intelligent systems; Informatics; Learning systems; Mathematics; Network topology; Neural networks; Pattern recognition; Performance analysis; Ensembles; Feature Selection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Hybrid Intelligent Systems, 2008. HIS '08. Eighth International Conference on
Conference_Location :
Barcelona
Print_ISBN :
978-0-7695-3326-1
Electronic_ISBN :
978-0-7695-3326-1
Type :
conf
DOI :
10.1109/HIS.2008.109
Filename :
4626695
Link To Document :
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