Abstract
The paper presents a critical comment on the rough sets approach to feature selection. It is highlighted that the small sample size may lead to spurious results in evaluating the feature subsets. Along with this, some attractive advantages of rough sets criteria are emphasized, and a new criterion is proposed. Two examples have been generated in order to demonstrate the flexibility of the proposed criterion and its advantages over some conventional criteria.
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References
Devijver P., J. Kittler (1982) Pattern Recognition. A statistical approach, Prentice Hall Int.
Dubois, D. and H. Prade (1990). Putting rough sets and fuzzy sets together, in: R. Slowiński (ed.) Intelligent Decision Support, Kluwer Academic Publishers/London, 203–232.
Dubois, D. and H. Prade (1987). Twofold fuzzy sets and rough sets — some issues in knowledge representation. Fuzzy Sets and Systems 23, 3–18.
Fibak, J., Z. Pawlak, K. Slowiński and R. Slowiński (1986). Rough sets based decision algorithm for treatment of duodenal ulcer by HSV. Bulletin of PAS 34, 227–248.
Kubat, M. (1989). Floating approximation in time-varying knowledge bases. Pattern Recognition Letters 10, 223–227.
Kuncheva, L. (1992). Fuzzy rough sets. Application to feature selection. Fuzzy Sets and Systems 51, 147–153.
Pawlak, Z. (1982). Rough sets. Int. Journal of Computer and Information Sciences 11, 341–356.
Pawlak, Z. (1985). Rough sets and fuzzy sets. Fuzzy Sets and Systems 17, 99–102.
Pawlak, Z. (1984). Rough classification. Int J Man-Machine Studies 20, 469–483.
Pawlak, Z., K. Slowiński, and R. Slowiński (1986). Rough classification of patients after highly selective vagotomy for duodenal ulcer. Int. J. Man-Machine Studies 24, 413–433.
Slowiński, K., R. Slowiński, and J. Stefanowski (1988). Rough sets approach to analysis of data from peritoneal lavage in acute pancreatitis. Med. Inform. 13, 143–159.
Slowiński, K. and R. Slowiński (1990). Sensitivity analysis of rough classification. Int. J. Man-Machine Studies 32, 693–705.
Valev V., Yu. Zhuravlev (1991). Integer-valued problems of transforming the training tables in k-valued code in pattern recognition problems, Pattern Recognition 24 283–288.
Wong, S.K.M. and W. Ziarko (1987). Comparison of the probabilistic approximate classification and the fuzzy set model. Fuzzy Sets and Systems 21, 357–362.
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© 1995 Springer-Verlag Berlin Heidelberg
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Kuncheva, L.I., Kounchev, R.K. (1995). On feature selection via rough sets. In: Hlaváč, V., Šára, R. (eds) Computer Analysis of Images and Patterns. CAIP 1995. Lecture Notes in Computer Science, vol 970. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60268-2_355
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DOI: https://doi.org/10.1007/3-540-60268-2_355
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Print ISBN: 978-3-540-60268-2
Online ISBN: 978-3-540-44781-8
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