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  • 标题:Knowledge discovery in data using formal concept analysis and random projections
  • 本地全文:下载
  • 作者:Cherukuri Aswani Kumar
  • 期刊名称:International Journal of Applied Mathematics and Computer Science
  • 电子版ISSN:2083-8492
  • 出版年度:2011
  • 卷号:21
  • 期号:4
  • DOI:10.2478/v10006-011-0059-1
  • 出版社:De Gruyter Open
  • 摘要:In this paper our objective is to propose a random projections based formal concept analysis for knowledge discovery in data. We demonstrate the implementation of the proposed method on two real world healthcare datasets. Formal Concept Analysis (FCA) is a mathematical framework that offers a conceptual knowledge representation through hierarchical conceptual structures called concept lattices. However, during the design of a concept lattice, complexity plays a major role.
  • 关键词:attribute implications; concept lattices; dimensionality reduction; formal concept analysis; knowledge discovery; random projections
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