Journal
INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE
Volume 21, Issue 4, Pages 745-756Publisher
UNIV ZIELONA GORA PRESS
DOI: 10.2478/v10006-011-0059-1
Keywords
attribute implications; concept lattices; dimensionality reduction; formal concept analysis; knowledge discovery; random projections
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Funding
- National Board of Higher Mathematics, Department of Atomic Energy, Government of India [2/48(11)2010-RD 11/10806]
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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.
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