Attribute Reduction Based on MapReduce Model and Discernibility Measure

被引：6

作者：

Czolombitko, Michal ^{[1
]}

Stepaniuk, Jaroslaw ^{[1
]}

机构：

[1] Bialystok Tech Univ, Fac Comp Sci, Wiejska 45A, PL-15351 Bialystok, Poland

来源：

COMPUTER INFORMATION SYSTEMS AND INDUSTRIAL MANAGEMENT, CISIM 2016 | 2016年 / 9842卷

关键词：

Rough sets; MapReduce; Reducts; Attribute reduction; Core;

D O I：

10.1007/978-3-319-45378-1_6

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper discusses two important problems of data reduction. The problems are related to computing reducts and core in rough sets. The authors use the fact that the necessary information about discernibility matrices can be computed directly from data tables, in the case of this paper so called counting tables are used. The discussed problems are of high computational complexity. Hence the authors propose to use the relevant heuristics, MRCR (MapReduce Core and Reduct Generation) implemented using the MapReduce model.

引用

页码：55 / 66

页数：12

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