Are Model-Based Clustering and Neural Clustering Consistent? A Case Study from Bioinformatics

Authors:
Davide Bacciu;Elia Biganzoli;Paulo J. Lisboa;Antonina Starita
Affiliations:
IMT Lucca Institute for Advanced Studies, Lucca, Italy 55100 and Dipartimento di Informatica, Università di Pisa, Pisa, Italy 56127;Division of Medical Statistics and Biometry, Istituto Nazionale per lo Studio e la Cura dei Tumori, , Milan, Italy;School of Computing and Mathematical Science, Liverpool John Moores University, Liverpool, UK;Dipartimento di Informatica, Università di Pisa, Pisa, Italy 56127
Venue:
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II
Year:
2008

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Abstract

A novel neural network clustering algorithm, CoRe, is benchmarked against previously published results on a breast cancer data set and applying the method of Partition Around Medoids (PAM). The data serve to compare the samples partitions obtained with the neural network, PAM and model-based algorithms, namely Gaussian Mixture Model (GMM), Variational Bayesian Gaussian Mixture (VBG) and Variational Bayesian Mixtures with Splitting (VBS). It is found that CoRe, on the one hand, agrees with the previously published partitions; on the other hand, it supports the existence of a supplementary cluster that we hypothesize to be an additional tumor subgroup with respect to those previously identified by PAM.