Abstract
In this work we check how the automatic discretization algorithms generate decision rules for the concrete medical problem — diagnosing mitochondrial encephalomyopathies (MEM).
We describe several algorithms for discretization — local and global — of continuous attributes obtained in the second stage of diagnosing MEM. All of these algorithms act together with the data analysis method based on the rough sets theory.
This work compares results — quality of classification rules — which were obtained using different discretization methods of the continuous attributes.
This work was supported by the Committee for Scientific Research, Warsaw, Poland, Grant No. 8T11C 005 12.
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References
Barkovich A. J.: “Toxic and metabolic brain disorders.” In: Pediatric Neuroimaging. Raven Press Ltd, New York, 1995.
Chan, C-C., Batur, C., Srinivassan, A.: “Determination of quantization intervals in rule based model for dynamic systems”, Proc. of the IEEE Conference on Systems, Man and Cybernetics, VA Oct.13–16, 1991, 1719–1723.
Chmielewski, M. R., Grzymala-Busse, J. W.: “Global Discretization of Continuous Attributes as Preprocessing for Inductive Learning”, Technical Report TR-92-7, Department of Computing Science, University of Cansas, Lawrence, USA, 1992.
Fayyad, U. M., Irani, K. B.: “On the handling of continuous-valued attributes in decision tree generation”, Machine Learning, 8(1992), 87–102.
Grzymala-Busse J.: “Managing Uncertainty in Expert Systems.” Kluwer Academic Publishers, 1992.
Grzymala-Busse J.: “LERS-a system for learning from examples based on Rough Sets. In R. Slowinski R. (ed.), In intelligent decision support. Handbook of Applications and Advances of the Rough Sets Theory, 3, Kluwer Academic Publishers, 1992.
Marszal-Paszek B., Paszek P., Wakulicz-Deja A.: “Applying Rough Sets to diagnose in Children’s Neurology.” Sixt International Conference Information Processing and Management of Uncertainty in Knowledge-Base System, Granada, Spain, 1996, Vol. 3, 1463–1468.
Matthews P. M., Anderman F., Silver K., Karpati G., Arnold D. L.: “Proton MR spectroscopic characterization of differences in regional brain metabolic abnormalities in mitochondrial encefalomyopathies.” Neurology 43 (1993), 2484–2490.
Paszek P., Wakulicz-Deja A.: “Optimalization Diagnose In Progressive Encephalopathy Applying The Rough Set Theory.” Four European Congress on Inteligent Techniques and Soft Computing, Aachen, Germany, 1996, Vol. 1, 192–196.
Pawlak Z.: “Rough Sets: Theoretical aspects of reasoning about data”, Boston: Kluwer Academic Publishers, 1991.
Skowron A., Rauszer G.: “The discernibility matrices and functions in information systems,” In R. Slowinski R. (ed.), In intelligent decision support. Handbook of Applications and Advances of the Rough Sets Theory, 331–336, Kluwer Academic Publishers, 1992.
Tulinius M. H., Holme E., Kristianson B., Larsson N., Oldfors A.: “Mitochondrial encephalomyopathies in childhood”, I. Biochemical and morphologic investigations. J. Pediatrics, 119, 242–50, 1991.
Wong, A. K. C., Chiu, D. K. Y.: “Synthesizing statistical knowledge from incomplete mixed-mode data”, IEEE Transaction on Pattern Analysis and Machine Intelligence, 9(1987), 796–805.
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© 1998 Springer-Verlag Berlin Heidelberg
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Wakulicz-Deja, A., Boryczka, M., Paszek, P. (1998). Discretization of Continuous Attributes on Decision System in Mitochondrial Encephalomyopathies. In: Polkowski, L., Skowron, A. (eds) Rough Sets and Current Trends in Computing. RSCTC 1998. Lecture Notes in Computer Science(), vol 1424. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-69115-4_66
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DOI: https://doi.org/10.1007/3-540-69115-4_66
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