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Topological reduction algorithm for relation systems
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AI
DOI：10.1007/s00500-022-07431-y.png)
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摘要
En 中文
A relation system, as an extension of information systems, is a significant form of representation and discovery of knowledge in rough set theory. Each relation system can induce a topological space. Topology is an invaluable tool for knowledge discovery in relation systems. In this paper, we use topological methods to study attribute reduction problems in relation systems. In the past studies, the topological reduction algorithm applied to arbitrary binary relations had not been proposed. To fill the gap, we propose the concept of topological reduction of relation systems based on binary relations without any other additional constraints. To identify all reductions, we define a discernibility matrix for this kind of reduction and develop its corresponding reduction algorithm. Finally, we conducted several experiments on five UCI datasets using six classification algorithms and two clustering algorithms to check our theoretical results. The experimental results show that our proposed algorithm is effective and practicable.
Keyword:
Topological reduction
Discernibility matrix
Relation system
Topological space
Rough set
期刊
IF:
2.5
论文数:
1.0W
被引数:
2.1W
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