|Table of Contents|

Accelerator for finding reduct based on attribute group

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2020年02期
Page:
216-223
Research Field:
Publishing date:

Info

Title:
Accelerator for finding reduct based on attribute group
Author(s):
Chen Yan1Song Jingjing12Yang Xibei1
1.School of Computer,Jiangsu University of Science and Technology,Zhenjiang 212003,China; 2.Key Laboratory of Data Science and Intelligent Application of Fujian Province University, Zhangzhou 363000,China
Keywords:
attribute groups attribute reduction bucket model neighborhood rough set
PACS:
TP181
DOI:
10.14177/j.cnki.32-1397n.2020.44.02.013
Abstract:
To improve the time efficiency of obtaining the reducts,based on the mechanism of bucket model,attributes are divided into different groups by considering the similarity between attributes. It follows that in the searching process of deriving reducts,attributes out of those groups containing at least one attribute in potential reducts should be evaluated,which can effectively reduce the searching space. Compared with the forward greedy searching approach,the experimental results show that the proposed strategy can significantly reduce the time consumption of obtaining reducts and the classification performance of reducts derived by using the strategy of attribute group is not decreased. This study provides a useful idea for accelerating the process of finding reducts.

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Last Update: 2020-04-20