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.
| Original language | English |
|---|---|
| Pages (from-to) | 193-217 |
| Number of pages | 25 |
| Journal | Fundamenta Informaticae |
| Volume | 167 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2019 |
Keywords
- Bicluster
- Boolean reasoning
- Continuous data biclustering
- Discernibility function
- Dissimilarity biclusters
- Prime implicants
- Similarity biclusters
ASJC Scopus subject areas
- Theoretical Computer Science
- Algebra and Number Theory
- Information Systems
- Computational Theory and Mathematics
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