Journal
INFORMATION SCIENCES
Volume 507, Issue -, Pages 772-794Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2019.06.064
Keywords
Three-way decisions; Confusion matrix; Measure; Classification; Rough set theory
Categories
Funding
- National Natural Science Foundation of China [61763031, 61673301, 61573255]
- National Key R&D Program of China [213]
- Major Project of Ministry of Public Security [20170004]
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Three-way decisions (3WD) is an important methodology in solving problems with uncertainty. A systematic analysis on three-way based uncertainty measures is conducive to the promotion of three-way decisions. Meanwhile, confusion matrix, with multifaceted views, serves as a fundamental role in evaluating classification performance. In this paper, confusion matrix is endowed with semantics of three-way decisions. A collection of measures are thus deduced and summarized into seven measure modes. We further investigate the formulation of three-way regions from a measure driven view. To satisfy the preferences of stakeholder, two different objective functions are formulated, and each of them can include different combinations of measures. To demonstrate the effectiveness, we generate probabilistic three-way decisions for a wealth of datasets. Compared with Gini coefficient based and Shannon entropy based objective functions, our model can deduce more satisfying three-way regions. (C) 2019 Elsevier Inc. All rights reserved.
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