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A Multiple-category Classification Approach with Decision-theoretic Rough Sets

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EN
Abstrakty
EN
By considering the levels of tolerance for errors and the cost of actions in real decision procedure, a new two-stage approach is proposed to solve the multiple-category classification problems with Decision-Theoretic Rough Sets (DTRS). The first stage is to change an m-category classification problem (m > 2) into an m two-category classification problem, and form three types of decision regions: positive region, boundary region and negative region with different states and actions by using DTRS. The positive region makes a decision of acceptance, the negative region makes a decision of rejection, and the boundary region makes a decision of abstaining. The second stage is to choose the best candidate classification in the positive region by using the minimum probability error criterion with Bayesian discriminant analysis approach. A case study of medical diagnosis demonstrates the proposed method.
Wydawca
Rocznik
Strony
173--188
Opis fizyczny
Bibliogr. 56 poz., tab.
Twórcy
autor
autor
autor
  • School of Economics andManagement, Southwest Jiaotong Univ., Chengdu, 610031, P.R. China, newton83@163.com
Bibliografia
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Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BUS8-0023-0044
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