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Neural Computing and Applications

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01-06-2013 | Original Article

Bi-clustering continuous data with self-organizing map

Authors: Khalid Benabdeslem, Kais Allab

Published in: Neural Computing and Applications | Issue 7-8/2013

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Abstract

In this paper, we present a new SOM-based bi-clustering approach for continuous data. This approach is called Bi-SOM (for Bi-clustering based on Self-Organizing Map). The main goal of bi-clustering aims to simultaneously group the rows and columns of a given data matrix. In addition, we propose in this work to deal with some issues related to this task: (1) the topological visualization of bi-clusters with respect to their neighborhood relation, (2) the optimization of these bi-clusters in macro-blocks and (3) the dimensionality reduction by eliminating noise blocks, iteratively. Finally, experiments are given over several data sets for validating our approach in comparison with other bi-clustering methods.

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Title: Bi-clustering continuous data with self-organizing map
Authors: Khalid Benabdeslem
Kais Allab
Publication date: 01-06-2013
Publisher: Springer-Verlag
Published in: Neural Computing and Applications / Issue 7-8/2013
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-012-1047-6

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