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《Journal of Chongqing University》 2008-01
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Merged Bayesian Theory of Rough Sets Recognition Method Research In Incomplete Information

ZHONG Bo,LUO Hui-Liang(College of Mathematics and Science,Chongqing University,Chongqing 400030,P.R.China)  
This research established a Bayesian decision criterion of minimum error rate based on rough sets in order to recognize effectively incomplete information.The work introduced rough sets Bayes' theorem and a combining rough sets reduction method.A statistics theory method for recognizing incomplete information pattern was derived.The computing tests of incomplete information recognition show the merged method of rough sets and Bayesian theory is more accurate and practical than either the discernibility matrix attribute reduction or Bayesian classifier recognition methods.
【Fund】: 重庆市自然基金资助项目(CSTC2005BB3169)
【CateGory Index】: TP182
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