Knowledge Granularity Attribute Reduction Algorithm for Incomplete Systems in a Clustering Context
Baohua Liang,
Erli Jin,
Liangfen Wei
et al.
Abstract:The phenomenon of missing data can be seen everywhere in reality. Most typical attribute reduction models are only suitable for complete systems. But for incomplete systems, we cannot obtain the effective reduction rules. Even if there are a few reduction approaches, the classification accuracy of their reduction sets still needs to be improved. In order to overcome these shortcomings, this paper first defines the similarities of intra-cluster objects and inter-cluster objects based on the tolerance principle … Show more
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