Abstract
There are lots of validation indexes and techniques to study clustering results. Biclustering algorithms have been applied in Systems Biology, principally in DNA Microarray analysis, for the last years, with great success. Nowadays, there is a big set of biclustering algorithms each one based in different concepts, but there are few intercomparisons that measure their performance. We review and present here some numerical measures, new and evolved from traditional clustering validation techniques, to allow comparisons and validation of biclustering algorithms.
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Santamaría, R., Quintales, L., Therón, R. (2007). Methods to Bicluster Validation and Comparison in Microarray Data. In: Yin, H., Tino, P., Corchado, E., Byrne, W., Yao, X. (eds) Intelligent Data Engineering and Automated Learning - IDEAL 2007. IDEAL 2007. Lecture Notes in Computer Science, vol 4881. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77226-2_78
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DOI: https://doi.org/10.1007/978-3-540-77226-2_78
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77225-5
Online ISBN: 978-3-540-77226-2
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