Abstract
The late iron age glass database consists of a significant proportion of the samples, classification of which is unknown. The data-mining methods such as the rule induction, the clusterization and the visualization are used in this paper to classify these samples to the one of the three main chronological periods (La Tene C1, La Tene C2, La Tene D1) of the glass artifacts. The results of the experiments performed with the C4.5 and the Ridor algorithms followed by the analysis conducted by domain experts indicate, that the unlabeled samples constitute a mixture of all classes in which LT C2 and LT D1 are in majority.
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© 2005 Springer-Verlag Berlin Heidelberg
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Grudziński, K., Karwowski, M. (2005). The Analysis of the Unlabeled Samples of the Iron Age Glass Data. 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_7
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DOI: https://doi.org/10.1007/3-540-32392-9_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25056-2
Online ISBN: 978-3-540-32392-1
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