Computer Science ›› 2016, Vol. 43 ›› Issue (Z6): 40-43.doi: 10.11896/j.issn.1002-137X.2016.6A.008

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Attribute Reduction Based on Cost Minimization and Significance of Joint Attributes

XU Fei-fei, BI Zhong-qin and LEI Jing-sheng   

  • Online:2018-12-01 Published:2018-12-01

Abstract: The classical rough set attribute reduction is mainly based on maintaining positive region,boundary region and negative region unchanged.In the decision rough set model,the reduction procedure for adding or deleting an attri-bute is no longer monotonous,so that three regions can not keep all unchanged.In decision theoretic rough set model,decision making should take consideration of minimizing the cost.Therefore,this paper put forward a method for attribute reduction based on minimizing the cost,while considering the classification ability of selected attribute subset to the decision-making,which is named as the significance of joint attributes.Experiments show that our method is effective.

Key words: Attribute reduction,Minimum cost,Significance of joint attributes,Decision rough sets

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