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Published in:
2014 | OriginalPaper | Chapter
Feature Group Weighting and Topological Biclustering
Authors : Tugdual Sarazin, Mustapha Lebbah, Hanane Azzag, Amine Chaibi
Published in: Neural Information Processing
Publisher: Springer International Publishing
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This paper proposes a new method to weight feature groups for biclustering. In this method, the observations and features are divided into biclusters, based on their characteristics. The weights are introduced to the biclustering process to simultaneously identify the relevance of feature groups in each bicluster. A new biclustering algorithm wBiTM (Weighted Biclustering Topological Map) is proposed. The new method is an extension to self-organizing map algorithm by adding the weight parameter and a new prototype for bicluster. Experimental results on synthetic data show the properties of the weights in wBiTM.