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.
@article{bwmeta1.element.bwnjournal-article-amcv21i4p745bwm,
author = {Cherukuri Aswani Kumar},
title = {Knowledge discovery in data using formal concept analysis and random projections},
journal = {International Journal of Applied Mathematics and Computer Science},
volume = {21},
year = {2011},
pages = {745-756},
language = {en},
url = {http://dml.mathdoc.fr/item/bwmeta1.element.bwnjournal-article-amcv21i4p745bwm}
}
Cherukuri Aswani Kumar. Knowledge discovery in data using formal concept analysis and random projections. International Journal of Applied Mathematics and Computer Science, Tome 21 (2011) pp. 745-756. http://gdmltest.u-ga.fr/item/bwmeta1.element.bwnjournal-article-amcv21i4p745bwm/
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