Instance Selection Using Evolutionary Algorithms: An Experimental Study

Author
Abstract

In this chapter, we carry out an empirical study of the performance of four representative evolutionary algorithm models considering two instance-selection perspectives, the prototype selection and the training set selection for data reduction in knowledge discovery. This study includes a comparison between these algorithms and other nonevolutionary instance-selection algorithms. The results show that the evolutionary instance-selection algorithms consistently outperform the nonevolutionary ones, offering two main advantages simultaneously, better instance-reduction rates and higher classification accuracy.

Year of Publication
2005
Number of Pages
127-152
Publisher
Springer London
City
London
ISBN Number
978-1-84628-183-9
URL
https://doi.org/10.1007/1-84628-183-0_5
DOI
10.1007/1-84628-183-0_5
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