DocumentCode
2961029
Title
Investigating the influence of RePART in ensemble systems designed by boosting
Author
Santos, Araken M. ; Canuto, Anne M P
Author_Institution
Inf. & Appl. Dept., Fed. Univ. of Rio Grande do Norte, Rio Grande
fYear
2008
fDate
1-8 June 2008
Firstpage
2907
Lastpage
2914
Abstract
This paper presents an investigation of the influence of the RePART (Reward and Punishment ARTmap) neural network in structures of ensembles designed by three variants of boosting: Aggressive, Conservative and Inverse Boosting. In this investigation, it is aimed to analyze whether the use of this model is positive for ARTMAP-based ensembles. In addition, it aims to define which boosting strategy is the most suitable to be used in ARTMAP-based ensembles.
Keywords
ART neural nets; decision trees; fuzzy neural nets; pattern classification; support vector machines; Reward and Punishment ARTmap neural network; aggressive boosting; conservative boosting; decision tree; ensemble systems; inverse boosting; k-nearest neighbour; support vector machine; Boosting; Neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location
Hong Kong
ISSN
1098-7576
Print_ISBN
978-1-4244-1820-6
Electronic_ISBN
1098-7576
Type
conf
DOI
10.1109/IJCNN.2008.4634207
Filename
4634207
Link To Document