吉林大学学报(工学版) ›› 2015, Vol. 45 ›› Issue (2): 583-588.doi: 10.13229/j.cnki.jdxbgxb201502036

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Single batch test algorithm on cost-sensitive uncertain Nave Bayes for uncertain data

ZHANG Xing1, LI Mei1, ZHANG Yang1,NING Ji-feng2   

  1. 1.College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling 712100, China;
    2.College of Information Engineering, Northwest A&F University, Yangling 712100, China
  • Received:2014-07-22 Online:2015-04-01 Published:2015-04-01

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Abstract: In this paper, we propose a single batch test algorithm on Cost-sensitive Uncertain Nave Bayes for Uncertain Data (SBT-CSUNB). We define the influence of an uncertain attribute on the total cost in cost-sensitive Nave Bayes Classifier, and put forward a method to fine an optimal batch test strategy. Experiment results on UCI Database demonstrate that the proposed algorithm can effectively reduce the total cost, and the performance is stable with different parameters and under high uncertain rate.

Key words: artificial intelligence, uncertain single batch, uncertain data, cost sensitive

CLC Number: 

  • TP391
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