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2017 | OriginalPaper | Buchkapitel

Optimization of Evolutionary Instance Selection

verfasst von : Mirosław Kordos

Erschienen in: Artificial Intelligence and Soft Computing

Verlag: 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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Metadaten
Titel
Optimization of Evolutionary Instance Selection
verfasst von
Mirosław Kordos
Copyright-Jahr
2017
DOI
https://doi.org/10.1007/978-3-319-59063-9_32