Affiliations: [a] Institute of Informatics, Silesian University of Technology, ul. Akademicka 16, 44-100 Gliwice, Poland. [email protected] | [b] Institute of Informatics, University of Warsaw, ul. Banacha, 02-097 Warsaw, Poland. [email protected]
Correspondence:
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Address for correspondence: Institute of Informatics, Silesian University of Technology, ul. Akademicka 16, 44-100 Gliwice, Poland.
Abstract: Biclustering is considered as the method of finding two–dimensional subgroups in a matrix of scalars. The paper introduces a new approach to biclustering continuous matrices on the basis of boolean function analysis. We draw the strong relation between inclusion–maximal (maximal with respect to inclusion) biclusters of the assumed maximal difference between the data in a bicluster and prime implicants of a boolean function describing the data. These biclusters are called similarity biclusters. In the opposition to them, a new notion of dissimilarity biclusters was also introduced in the paper.
Keywords: bicluster, boolean reasoning, discernibility function, prime implicants, similarity biclusters, dissimilarity biclusters, continuous data biclustering
