Accuracy and robustness of clustering algorithms for small-size applications in bioinformatics |
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Authors: | Pamela Minicozzi Enrico Scalas Francesco Dondero |
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Affiliation: | a Department of Advanced Sciences and Technology, Università degli Studi del Piemonte Orientale, via Bellini 25g, 15100 Alessandria, Italy b Department of Life and Environmental Science, Università degli Studi del Piemonte Orientale, via Bellini 25g, 15100 Alessandria, Italy |
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Abstract: | The performance (accuracy and robustness) of several clustering algorithms is studied for linearly dependent random variables in the presence of noise. It turns out that the error percentage quickly increases when the number of observations is less than the number of variables. This situation is common situation in experiments with DNA microarrays. Moreover, an a posteriori criterion to choose between two discordant clustering algorithm is presented. |
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Keywords: | 02.50.Sk 87.18.Wd 87.18.Tt 87.10.Rt |
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