Applying Static and Dynamic Weight Measures in Ensemble Systems

Author

Paradeda, Raul ; Xavier, Joao C. ; Canuto, Anne M P

Author_Institution

Inf. & Appl. Math. Dept., Fed. Univ. of Rio Grande do Norte, Natal

fYear

2008

fDate

26-30 Oct. 2008

Firstpage

45

Lastpage

50

Abstract

It is well known that the use of ensemble systems usually increases the accuracy rate of individual machine learning systems. A way of improving the accuracy of these systems even further is through the use of weight measures. This paper analyzes the influence of the use of static and dynamic weights in the accuracy of two structures (homogeneous and heterogeneous) of ensemble systems. Furthermore, it investigates the relation between diversity and the use weights in ensemble system.

Keywords

learning (artificial intelligence); pattern classification; dynamic weight measures; ensemble system; heterogeneous structure; homogeneous structure; machine learning system; multiclassifier system; static weight measures; Classification algorithms; Diversity reception; Informatics; Learning systems; Mathematics; Neural networks; Pattern recognition; Robustness; Testing; Weight measurement; Dynamic Weights; Ensemble Systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2008. SBRN '08. 10th Brazilian Symposium on

Conference_Location

Salvador

ISSN

1522-4899

Print_ISBN

978-1-4244-3219-6

Electronic_ISBN

1522-4899

Type

conf

DOI

10.1109/SBRN.2008.35

Filename

4665890