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Rough sets and ordinal reducts

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Abstract

Rough set theory has been successfully applied in selecting attributes to improve the effectiveness in deriving decision trees/rules for decisions and classification problems. When decisions involve ordinal classes, the rough set reduction process should try to preserve the order relation generated by the decision classes. Previous works on rough sets when applied to ordinal decision systems still focus on preserving the information relating to the decision classes and not the underlying order relation. In this paper, we propose a new way of evaluating and finding reducts involving ordinal decision classes which focus on the order generated by the ordinal decision classes.

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Notes

  1. We use X/Y to represent difference of set X and Y.

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Acknowledgements

This project is supported by the Hong Kong Polytechnic University research grant H-ZJ85.

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Authors and Affiliations

  1. Department of Computing, Hong Kong Polytechnic University, Hong Kong, China

    John W. T. Lee, Daniel S. Yeung & Eric C. C. Tsang

Authors
  1. John W. T. Lee
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  2. Daniel S. Yeung
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  3. Eric C. C. Tsang
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Corresponding author

Correspondence to John W. T. Lee.

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Lee, J.W.T., Yeung, D.S. & Tsang, E.C.C. Rough sets and ordinal reducts. Soft Comput 10, 27–33 (2006). https://doi.org/10.1007/s00500-005-0460-5

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  • DOI: https://doi.org/10.1007/s00500-005-0460-5

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