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Determining Thresholds in Three-Way Decisions: A Multi-object Optimization View

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Rough Sets (IJCRS 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10314))

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Abstract

Determination of thresholds is recognized as a fundamental problem in decision-theoretic rough sets. Traditionally, thresholds are determined by observing Bayesian decision theory. Although the semantic seems to be enriched as compared to probabilistic rough sets, the functionality of risk is not comprehensively explored. In allusion to this situation, we develop a multi-object optimization view based model on determining thresholds. By generalizing the expected loss function to target function, this model claims that thresholds in three-way are radically constructed by pair-wise region-based target functions. By transferring the principle of pair-wise region-based target functions on multi-quantitative scenario, we present a finer-grained formulation for thresholds solving. Furthermore, we investigate the multi-layer of presented model. Finally, the optimistic and pessimistic multi-quantitative decision-theoretic rough set is defined to illustrate the value of presented model.

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Acknowledgements

The authors would like to thank the anonymous reviewers for their constructive comments that help improve the manuscript. This research was supported by the National Natural Science Foundation of China (No. 61273304, 61673301, 61573255, 61573259), the Specialized Research Fund for the Doctoral Program of Higher Education of China (No. 20130072130004), and Natural Science Foundation of Shanghai (No. 14ZR1442600).

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Correspondence to Duoqian Miao .

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Zhang, Y., Miao, D., Xu, J., Zhang, Z. (2017). Determining Thresholds in Three-Way Decisions: A Multi-object Optimization View. In: Polkowski, L., et al. Rough Sets. IJCRS 2017. Lecture Notes in Computer Science(), vol 10314. Springer, Cham. https://doi.org/10.1007/978-3-319-60840-2_24

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  • DOI: https://doi.org/10.1007/978-3-319-60840-2_24

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  • Print ISBN: 978-3-319-60839-6

  • Online ISBN: 978-3-319-60840-2

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