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2017 | OriginalPaper | Chapter

Optimization of Evolutionary Instance Selection

Author : Mirosław Kordos

Published in: Artificial Intelligence and Soft Computing

Publisher: Springer International Publishing

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Abstract

Evolutionary instance selection is the most accurate process comparing to other methods based on distance, such as the instance selection methods based on k-NN. However, the drawback of evolutionary methods is their very high computational cost. We compare the performance of evolutionary and classical methods and discuss how to minimize the computational cost using optimization of genetic algorithm parameters, joining them with the classical instance selection methods and caching the information used by k-NN.

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Metadata
Title
Optimization of Evolutionary Instance Selection
Author
Mirosław Kordos
Copyright Year
2017
Book
Artificial Intelligence and Soft Computing

Print ISBN: 978-3-319-59062-2

Electronic ISBN: 978-3-319-59063-9

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-59063-9_32

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