Abstract
The paper presents a comparison study of the rough sets approach and probabilistic techniques, in particular, discriminant analysis and probabilistic inductive learning, to data analysis on a common set of medical data. This study completes the comparison done in [9], by taking into account, in addition to the location model of discriminant analysis, the linear Fisherian discrimination and Bayesian tree classifiers derived via inductive learning approach. A general discussion on similarities and differences among compared methods is given. Particular attention is paid to data reduction and creation of decision rules. The outcomes of a computational experiment on the common set of data are described and discussed.
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References
Cestnik B., Kononenko I., Bratko I., ASSISTANT86, a knowledge-elicitation tool for sophisticated users. In Bratko I., Lavrac N. (eds), Progress in Machine Learning, Sigma Press, Wilmshow (1987) (distributed by Wiley), 31–45.
Fibak J., Pawlak Z., Słowiński K., Slowinski K., Rough sets based decision algorithm for treatment of duodenal ulcer by HSV. Bull. PAS, Biological Series 34, 10–12 (1986), 227–246.
Gale J., Marsden P., Diagnosis process not conduct. In Sheldon M., Brook J., Rector A. (eds), Decision Making in General Practice, Macmillan (1985).
Garns M., Lavrac N., Review of five empirical learning systems within a proposed schemata, In Bratko I., Lavrac N. (eds) Progress in Machine Learning, Sigma Press, Wilmshow (1987) (distributed by Wiley), 46–66.
Haberman S.J., Log linear fit for contingency tables. Algorithm AS51. Applied Statistics 21 (1972), 218–225.
Gruszecki G., Słowiński R., Stefanowski J., Rough DAS — Rough Sets Based Data Analysis Software — user’s manual. APRO S.A. Warszawa (1990).
Krusińska E., New procedure for selection of variables in location model for mixed variable discrimination. Biometrical Journal 31 (1989), 511–523.
Krusińska E., Linear and quadratic classification rule in the location model. A comparison for heterogeneous data. Biocybernetics and Biomedical Engineering 9 (1989), 103–113.
Krusińska E., Słowiński R., Stefanowski J., Discriminat versus rough sets approach to vague data analysis. Applied Stochastic Models and Data Analysis 8, (1992) (to appear).
Krzanowski W.J., Discrimination and classification using both binary and continuous variables. J. Am. Statistic Assoc. 70 (1975), 782–790.
Lachenburch P.A., Discriminant Analysis, Hafner Press, New York (1975).
Man J., Kononenko B., Cestnik I., Bratko I., Assistant Proffesional. User’s manual. Institute Jozef Stefan, Ljubliana (1988).
Niblet T., Construction of decision trees in noisy domains, in Bratko I., Lavrac N. (eds) Progress in Machine Learning, Sigma Press, Wilmshow (1987) (distributed by Wiley).
Nowicki R., Słowiński R., Stefanowski J., Rough sets analysis of diagnostic capacity of vibroacoustic symptoms, Computers and Mathematics with Applications (1992) (to appear).
Nowicki R., Słowiński R., Stefanowski J., Evaluation of vibroacoustic symptoms by means of the rough sets theory, Computer in Industry (1992) (submitted).
Pawlak Z., Rough sets. International Journal of Information and Computer Sciences 11, 5 (1982), 341–356.
Pawlak Z., Słowiński K., Slowinski R., Rough classification of patients after highly selective vagotomy for duodenal ulcer. International Journal of Man-Machine Studies 24 (1986), 413–433.
Słowiński K., Słowiński R., Stefanowski J., Rough sets approach to analysis of data from pertioneal lavage in acute pancreatitis. Medical Informatics 13, 3 (1989), 143–159.
Słowiński K., Słowiński R., Sensitivity analysis of rough classification. International Journal of Man-Machine Studies 32 (1990), 693–705.
Stefanowski J., Rough classification and discriminant analysis. Comparative study. (in Polish) Postçpy Cybernetyki (1991) (to appear).
Stefanowski J., Classification support based on the rough sets theory, Proceedings of the IIASA Workshop on User-Oriented Methodology and Techniques of Decision Analysis and Support. Serock, 9–13 Sept. (1991) (to appear).
Watkins C.J. C.H., Combining cross-validation and search. In Bratko I., Lavrac N. (eds) Progress in Machine Learning. Sigma Press, Wilmshow 1987 (distributed by Wiley) 79–97.
SPSSX, Statistical Algorithms. SPSS Inc. Chicago (1983) Mc Graw-Hill
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© 1992 Springer Science+Business Media Dordrecht
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Krusińska, E., Babic, A., Słowiński, R., Stefanowski, J. (1992). Comparison of the Rough Sets Approach and Probabilistic Data Analysis Techniques on a Common Set of Medical Data. 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_16
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DOI: https://doi.org/10.1007/978-94-015-7975-9_16
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-4194-4
Online ISBN: 978-94-015-7975-9
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