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2018 | OriginalPaper | Buchkapitel

A Comparison of Characteristic Sets and Generalized Maximal Consistent Blocks in Mining Incomplete Data

verfasst von : Patrick G. Clark, Cheng Gao, Jerzy W. Grzymala-Busse, Teresa Mroczek

Erschienen in: Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations

Verlag: Springer International Publishing

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Abstract

We discuss two interpretations of missing attribute values, lost values and “do not care” conditions. Both interpretations may be used for data mining based on characteristic sets. On the other hand, maximal consistent blocks were originally defined for incomplete data sets with “do not care” conditions, using only lower and upper approximations. We extended definitions of maximal consistent blocks to both interpretations while using probabilistic approximations, a generalization of lower and upper approximations. Our main objective is to compare approximations based on characteristic sets with approximations based on maximal consistent blocks in terms of an error rate.

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Vorheriges Kapitel Defuzzyfication in Interpretation of Comparator Networks

Nächstes Kapitel Rules Induced from Rough Sets in Information Tables with Continuous Values

Clark, P.G., Gao, C., Grzymala-Busse, J.W., Mroczek, T.: Characteristic sets and generalized maximal consistent blocks in mining incomplete data. In: Polkowski, L., Yao, Y., Artiemjew, P., Ciucci, D., Liu, D., Ślęzak, D., Zielosko, B. (eds.) IJCRS 2017. LNCS (LNAI), vol. 10313, pp. 477–486. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-60837-2_39CrossRef

Clark, P.G., Grzymala-Busse, J.W.: Experiments on probabilistic approximations. In: Proceedings of the 2011 IEEE International Conference on Granular Computing, pp. 144–149 (2011)

Clark, P.G., Grzymala-Busse, J.W., Rzasa, W.: Mining incomplete data with singleton, subset and concept approximations. Inf. Sci. 280, 368–384 (2014)MathSciNetCrossRef

Grzymala-Busse, J.W.: MLEM2: a new algorithm for rule induction from imperfect data. In: Proceedings of the 9th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, pp. 243–250 (2002)

Grzymala-Busse, J.W.: Rough set strategies to data with missing attribute values. In: Notes of the Workshop on Foundations and New Directions of Data Mining, in Conjunction with the Third International Conference on Data Mining, pp. 56–63 (2003)

Grzymala-Busse, J.W.: Three approaches to missing attribute values–a rough set perspective. In: Proceedings of the Workshop on Foundation of Data Mining, in Conjunction with the Fourth IEEE International Conference on Data Mining, pp. 55–62 (2004)

Grzymała-Busse, J.W.: Generalized parameterized approximations. In: Yao, J.T., Ramanna, S., Wang, G., Suraj, Z. (eds.) RSKT 2011. LNCS (LNAI), vol. 6954, pp. 136–145. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-24425-4_20CrossRef

Grzymala-Busse, J.W., Ziarko, W.: Data mining based on rough sets. In: Wang, J. (ed.) Data Mining: Opportunities and Challenges, pp. 142–173. Idea Group Publishing, Hershey (2003)CrossRef

Leung, Y., Li, D.: Maximal consistent block technique for rule acquisition in incomplete information systems. Inf. Sci. 153, 85–106 (2003)MathSciNetCrossRef

10.

Leung, Y., Wu, W., Zhang, W.: Knowledge acquisition in incomplete information systems: a rough set approach. Eur. J. Oper. Res. 168, 164–180 (2006)MathSciNetCrossRef

11.

Liang, J.Y., Wang, B.L., Qian, Y.H., Li, D.Y.: An algorithm of constructing maximal consistent blocks in incomplete information systems. Int. J. Comput. Sci. Knowl. Eng. 2(1), 11–18 (2008)

12.

Liu, X., Shao, M.: Approachs to computing maximal consistent block. In: Wang, X., Pedrycz, W., Chan, P., He, Q. (eds.) ICMLC 2014. CCIS, vol. 481, pp. 264–274. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-662-45652-1_27CrossRef

13.

Pawlak, Z., Skowron, A.: Rough sets: some extensions. Inf. Sci. 177, 28–40 (2007)MathSciNetCrossRef

14.

Pawlak, Z., Wong, S.K.M., Ziarko, W.: Rough sets: probabilistic versus deterministic approach. Int. J. Man Mach. Stud. 29, 81–95 (1988)CrossRef

15.

Ślȩzak, D., Ziarko, W.: The investigation of the Bayesian rough set model. Int. J. Approx. Reason. 40, 81–91 (2005)MathSciNetCrossRef

16.

Wong, S.K.M., Ziarko, W.: INFER–an adaptive decision support system based on the probabilistic approximate classification. In: Proceedings of the 6th International Workshop on Expert Systems and their Applications, pp. 713–726 (1986)

17.

Yao, Y.Y.: Probabilistic rough set approximations. Int. J. Approx. Reason. 49, 255–271 (2008)CrossRef

18.

Yao, Y.Y., Wong, S.K.M.: A decision theoretic framework for approximate concepts. Int. J. Man Mach. Stud. 37, 793–809 (1992)CrossRef

19.

Ziarko, W.: Variable precision rough set model. J. Comput. Syst. Sci. 46(1), 39–59 (1993)MathSciNetCrossRef

20.

Ziarko, W.: Probabilistic approach to rough sets. Int. J. Approx. Reason. 49, 272–284 (2008)MathSciNetCrossRef

Titel: A Comparison of Characteristic Sets and Generalized Maximal Consistent Blocks in Mining Incomplete Data
verfasst von: Patrick G. Clark
Cheng Gao
Jerzy W. Grzymala-Busse
Teresa Mroczek
Verlag: Springer International Publishing
Buch: Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations
Print ISBN: 978-3-319-91475-6

Electronic ISBN: 978-3-319-91476-3

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-319-91476-3_40

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