Abstract
The goal of the paper is to compare the performance of instance reduction algorithms (IRA) with other approaches. The paper briefly describes a family of instance reduction algorithms proposed by the authors. To evaluate their performance the computational experiment is carried out. The experiment involves comparing a performance of IRA with several other approaches using alternative machine learning classification tools.
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Czarnowski, I., Jędrzejowicz, P. (2005). Family of Instance Reduction Algorithms Versus Other Approaches. In: Kłopotek, M.A., Wierzchoń, S.T., Trojanowski, K. (eds) Intelligent Information Processing and Web Mining. Advances in Soft Computing, vol 31. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32392-9_3
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DOI: https://doi.org/10.1007/3-540-32392-9_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25056-2
Online ISBN: 978-3-540-32392-1
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