Abstract
Biclustering is an important method of processing a big amount of data. In this paper, hierarchical structures of biclusters and their advantages are discussed. We propose the author’s method called HEMBI (Hierarchical Evolutionary Multi-Biclustering) which creates this kind of structures. The HEMBI uses an Evolutionary Algorithm to split a data space into a restricted number of regions. The important feature of the method is ability to choice the optimal number of biclusters, which is restricted only to a maximum value. The conducted experiments and their results are presented and discussed.
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Filipiak, A.M., Kwasnicka, H. (2016). Hierarchical Evolutionary Multi-biclustering. In: Nguyen, N.T., Trawiński, B., Fujita, H., Hong, TP. (eds) Intelligent Information and Database Systems. ACIIDS 2016. Lecture Notes in Computer Science(), vol 9621. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49381-6_64
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DOI: https://doi.org/10.1007/978-3-662-49381-6_64
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