Abstract
Objects in an information system analyzed by the rough sets theory methods are characterized by attributes, which can take on a finite set of values only. In diagnostic experiments, condition attributes are usually treated as continuous variables, taking values from certain intervals. So, to use this theory in such problems, certain discretization (coding) of continuous variables is needed. The optimal classification properties of an information system were taken by the authors as base criteria for selecting discretization. The concepts of a random information system and of an expected value of classification quality were introduced. The method of finding suboptimal discretizations based on these concepts is presented and is illustrated with data from concretes’ frost resistance investigations.
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References
Pawlak, Z. (1991) Rough Sets: Theoretical Aspects of Reasoning about Data, Kluwer Academic Publisher, Dordrecht.
Zygadlo, M. and Piasta, Z. (1988) ‘Indirect assessment of frost durability of ceramics’, Industrial Ceramics 8, 129–133.
Zygadlo, M., Piasta, Z. and Lenarcik, A. (1991) ‘A method of diagnostic of brittle materials frost resistance examplified by ceramic bricks’, in A.M Brandt and I.H. Marshall (eds.), Brittle Matrix Composites 3, Elsevier Applied Science, London and New York, pp. 377–385.
Roy, C., Maslouhi, A., Gaucher, D. and Piasta, Z. (1988) ‘Classification of acoustic emission sources in CFRP assisted by pattern recognition analysis’, Canadian Aeronautics and Space Journal 34, 224–232.
Roy, C., Maslouhi, A., Allard, J. and Piasta, Z. (1991) ‘Pattern recognition character- ization of microfailures in composites via analytical quantitative acoustic emission’, in A.H. Cardon and G. Verchery (eds.), Durability of Polymer Based Composite Systems for Structural Applications, Elsevier Applied Science, London and New York, pp. 312–324.
Feknous, N., Ballivy, G. and Piasta, Z. (1989) ‘Monitoring of damaged injected rock with acoustic emission technique’, Proceedings of Conference on Recent Developments on the Facture of Concrete and Rock, Elsevier Applied Science, London.
Piasta, Z. (1991) ‘Diagnostic classification for brittle matrix composites assisted by pattern recognition and rough sets analysis’, in A.M Brandt and I.H. Marshall (eds.), Brittle Matrix Composites 3, Elsevier Applied Science, London and New York, pp.258268.
Pawlak, Z., Wong, S.K.M. and Ziarko, W., (1988) ‘Rough sets: probabilistic versus deterministic approach’, International Journal of Man-Machine Studies 29, 81–95.
Piasta, Z. and Rusin, Z., (1986) ‘Evaluation of standard methods for examining usefulness of aggregates for frost resistant concretes’, Budownictwo 22, Kielce University of Technology, 119–126 (in Polish).
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© 1992 Springer Science+Business Media Dordrecht
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Lenarcik, A., Piasta, Z. (1992). Discretization of Condition Attributes Space. In: Słowiński, R. (eds) Intelligent Decision Support. Theory and Decision Library, vol 11. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-7975-9_23
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DOI: https://doi.org/10.1007/978-94-015-7975-9_23
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-4194-4
Online ISBN: 978-94-015-7975-9
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