KNOWLEDGE DISCOVERY IN DATA USING FORMAL CONCEPT ANALYSIS AND RANDOM PROJECTIONS
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.
knowledge discovery formal concept analysis random projections concept lattices attribute implications dimensionality reduction