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The Feature Core of Dynamic Reduct

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DOI: 10.4236/am.2012.35073    3,030 Downloads   5,127 Views   Citations
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ABSTRACT

To the reduct problems of decision system, the paper proposes the notion of dynamic core according to the dynamic reduct model. It describes various formal definitions of dynamic core, and discusses some properties about dynamic core. All of these show that dynamic core possesses the essential characters of the feature core.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

J. Wang, "The Feature Core of Dynamic Reduct," Applied Mathematics, Vol. 3 No. 5, 2012, pp. 484-488. doi: 10.4236/am.2012.35073.

References

[1] Z. Pawlak, “Rough Sets (Periodical Style),” International Journal of Computer and Information Sciences, Vol. 11, No. 5, 1982, pp. 341-356. doi:10.1007/BF01001956
[2] X. H. Hu, and N. Cercone, “Learning in Relational Databases: A Rough Set Approach (Periodical Style),” International Journal of Computational Intelligence, Vol. 11, No. 2, 1995, pp. 323-338.
[3] J. Jelonek, K. Krawiec and R. Slowinski, “Rough Set Reduction of Attributes and Their Domains for Neural Networks (Periodical Style),” Computational Intelligence, Vol. 11, No. 2, 1995, pp. 339-347. doi:10.1111/j.1467-8640.1995.tb00036.x
[4] J. G. Bazan, “A Comparison of Dynamic and Non-Dynamic Rough Set Methods for Extracting Laws from Decision Tables (Published Conference Proceedings Style),” In: L. Polkowski and A. Skowron, Eds., Rough Sets in Knowledge Discovery 1: Methodology and Applications, Physica-Verlag, Heidelberg, 1998, pp. 321-365.
[5] J. G. Bazan, A. Skowron and P. Synak, “Dynamic Reducts as a Tool for Extracting Laws from Decision Tables, in: Methodologies for Intelligent System (Published Conference Proceedings Style),” Proceedings of 8th International Symposium ISMIS’94, Vol. 869, Springer-Verlag, Berlin, 1994, pp. 346-355.
[6] Z. Pawlak, “Rough Sets (Periodical Style),” International Journal of Computer and Information Sciences, Vol. 11, No. 5, 1982, pp. 341-356. doi:10.1007/BF01001956
[7] X. H. Hu, and N. Cercone, “Learning in Relational Databases: A Rough Set Approach (Periodical Style),” International Journal of Computational Intelligence, Vol. 11, No. 2, 1995, pp. 323-338.
[8] J. Jelonek, K. Krawiec and R. Slowinski, “Rough Set Reduction of Attributes and Their Domains for Neural Networks (Periodical Style),” Computational Intelligence, Vol. 11, No. 2, 1995, pp. 339-347. doi:10.1111/j.1467-8640.1995.tb00036.x
[9] J. G. Bazan, “A Comparison of Dynamic and Non-Dynamic Rough Set Methods for Extracting Laws from Decision Tables (Published Conference Proceedings Style),” In: L. Polkowski and A. Skowron, Eds., Rough Sets in Knowledge Discovery 1: Methodology and Applications, Physica-Verlag, Heidelberg, 1998, pp. 321-365.
[10] J. G. Bazan, A. Skowron and P. Synak, “Dynamic Reducts as a Tool for Extracting Laws from Decision Tables, in: Methodologies for Intelligent System (Published Conference Proceedings Style),” Proceedings of 8th International Symposium ISMIS’94, Vol. 869, Springer-Verlag, Berlin, 1994, pp. 346-355.

  
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