Abstract
The monograph is devoted to the study of inhibitory rules. In contrast to deterministic (standard) rules which have the relation attribute = value on the right-hand side, inhibitory rules have on the right-hand side the relation attibute ≠ value. For information systems [60, 63, 72], we consider inhibitory association rules which on the right-hand side can have an arbitrary attribute. For decision systems (decision tables) [60], we consider inhibitory decision rules containing on the right-hand side the decision attribute. It is worthwhile mentioning that in the rough set approach the decision rules are used for extension of approximations of concepts from given samples of objects on the whole universe of objects (see, e.g., [5, 6, 75]).
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© 2009 Springer-Verlag Berlin Heidelberg
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Delimata, P., Moshkov, M.J., Skowron, A., Suraj, Z. (2009). Introduction. In: Inhibitory Rules in Data Analysis. Studies in Computational Intelligence, vol 163. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85638-2_1
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DOI: https://doi.org/10.1007/978-3-540-85638-2_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85637-5
Online ISBN: 978-3-540-85638-2
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