Knowledge discovery in data using formal concept analysis and random projections - Aswani Kumar, Cherukuri (Zielona Góra: Uniwersytet Zielonogórski)
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.
Keywords: attribute implications; concept lattices; dimensionality reduction; formal concept analysis; knowledge discovery; random projections