Factor Analysis of Incidence Data via Novel Decomposition of Matrices
ICFCA '09 Proceedings of the 7th International Conference on Formal Concept Analysis
Discovery of optimal factors in binary data via a novel method of matrix decomposition
Journal of Computer and System Sciences
Triadic Concept Analysis of Data with Fuzzy Attributes
GRC '10 Proceedings of the 2010 IEEE International Conference on Granular Computing
Optimal Factorization of Three-Way Binary Data
GRC '10 Proceedings of the 2010 IEEE International Conference on Granular Computing
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We present a comparison between Hierarchical Classes Analysis and the formal concept analytical approach to Factor Analysis regarding the factorization problem of binary matrices. Both methods decompose a binary matrix into the Boolean matrix product of two binary matrices such that the number of factors is as small as possible. We show that the two approaches yield the same decomposition even though the methods are different. The main aim of this paper is to connect the two fields as they produce the same results and we show how the two domains can benefit from one another.