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Type: Artigo
Title: On bicluster aggregation and its benefits for enumerative solutions
Author: Oliveira, Saullo
Veroneze, Rosana
Von Zuben, Fernando J.
Abstract: Biclustering involves the simultaneous clustering of objects and their attributes, thus defining local two-way clustering models. Recently, efficient algorithms were conceived to enumerate all biclusters in real-valued datasets. In this case, the solution composes a complete set of maximal and non-redundant biclusters. However, the ability to enumerate biclusters revealed a challenging scenario: in noisy datasets, each true bicluster may become highly fragmented and with a high degree of overlapping. It prevents a direct analysis of the obtained results. Aiming at reverting the fragmentation, we propose here two approaches for properly aggregating the whole set of enumerated biclusters: one based on single linkage and the other directly exploring the rate of overlapping. Both proposals were compared with each other and with the actual state-of-the-art in several experiments, and they not only significantly reduced the number of biclusters but also consistently increased the quality of the solution
Subject: Valores estranhos (Estatistica)
Aprendizado de máquina
Análise por agrupamento
Mineração de dados (Computação)
Country: Alemanha
Editor: Springer
Rights: Aberto
Identifier DOI: 10.1007/978-3-319-21024-7_18
Date Issue: 2015
Appears in Collections:FEEC - Artigos e Outros Documentos

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