Journal
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
Volume 55, Issue 1, Pages 197-210Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ijar.2013.02.013
Keywords
Decision-theoretic rough sets; Binary logistic analysis; Multivariate logistic regression; Decision making
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Funding
- National Science Foundation of China [71201133, 61175047, 71090402/G1]
- Youth Social Science Foundation of the Chinese Education Commission [11YJC630127]
- Research Fund for the Doctoral Program of Higher Education of China [20120184120028]
- China Postdoctoral Science Foundation [2012M520310]
- Fundamental Research Funds for the Central Universities of China [SWJTU12CX117]
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Logistic regression analysis is an effective approach to the classification problem. However, it may lead to high misclassification rate in real decision procedures. Decision-Theoretic Rough Sets (DTRS) employs a three-way decision to avoid most direct misclassification. We integrate logistic regression and DTRS to provide a new classification approach. On one hand, DTRS is utilized to systematically calculate the corresponding thresholds with Bayesian decision procedure. On the other hand, logistic regression is employed to compute the conditional probability of the three-way decision. The empirical studies of corporate failure prediction and high school program choices' prediction validate the rationality and effectiveness of the proposed approach. (C) 2013 Elsevier Inc. All rights reserved.
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