Abstract
The three-way decision theory (3WD) is constructed based on the notions of the acceptance, rejection or non-commitment, which can be directly generated by the three regions: positive region (POS), negative region (NEG) and boundary region (BND). At present, how to process the boundary region has become a hot topic in the field of three-way decision theory. Although several methods have been proposed to address this problem, most of them don’t take cost-sensitive classification into consideration. In this paper, we adopt a cost-sensitive method to deal with the boundary region. Under the principle of reducing loss of classification, we adjust the border distance which is between sample of boundary region and the cover through introducing a cost-sensitive distance coefficient \(\eta \). The coefficient \(\eta \) can be automatically calculated according to the distribution characteristics of samples. Compared with other models, experimental results show that our model can obtain high correct classification rate. What’s more, our model can reduce loss of classification by improving the recall rate of high cost sample when dealing with the boundary region.
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Acknowledgments
This work is supported by the National Natural Science Foundation of China (No. 61175046, No. 61402006), supported by Provincial Natural Science Research Program of Higher Education Institutions of Anhui Province (No. KJ2013A016), and supported by Open Funding Project of Co-Innovation Center for Information Supply & Assurance Technology of Anhui University (No. ADXXBZ201410), and supported by the Provincial Natural Science Foundation of Anhui Province (No. 1508085MF113).
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Zhang, Y. et al. (2016). Research on Cost-Sensitive Method for Boundary Region in Three-Way Decision Model. In: Flores, V., et al. Rough Sets. IJCRS 2016. Lecture Notes in Computer Science(), vol 9920. Springer, Cham. https://doi.org/10.1007/978-3-319-47160-0_24
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DOI: https://doi.org/10.1007/978-3-319-47160-0_24
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