by Keyword: Cluster validity

Falasconi, M., Gutierrez, A., Pardo, M., Sberveglieri, G., Marco, S., (2010). A stability based validity method for fuzzy clustering Pattern Recognition , 43, (4), 1292-1305

An important goal in cluster analysis is the internal validation of results using an objective criterion. Of particular relevance in this respect is the estimation of the optimum number of clusters capturing the intrinsic structure of your data. This paper proposes a method to determine this optimum number based on the evaluation of fuzzy partition stability under bootstrap resampling. The method is first characterized on synthetic data with respect to hyper-parameters, like the fuzzifier, and spatial clustering parameters, such as feature space dimensionality, clusters degree of overlap, and number of clusters. The method is then validated on experimental datasets. Furthermore, the performance of the proposed method is compared to that obtained using a number of traditional fuzzy validity rules based on the cluster compactness-to-separation criteria. The proposed method provides accurate and reliable results, and offers better generalization capabilities than the classical approaches.

JTD Keywords: Fuzzy c-means, Cluster validity, Number of clusters, Cluster stability

Falasconi, M., Gutierrez, A., Auffarth, B., Sberveglieri, G., Marco, S., (2009). Cluster analysis of the rat olfactory bulb activity in response to different odorants Olfaction and Electronic Nose: Proceedings of the 13th International Symposium on Olfaction and Electronic Nose 13th International Symposium on Olfaction and the Electronic Nose (ed. Pardo, M., Sberveglieri, G.), Amer Inst Physics (Brescia, Italy) 1137, 169-172

With the goal of deepen in the understanding of coding of chemical information in the olfactory system, a large data set consisting of rat's olfactory bulb activity values in response to several different volatile compounds has been analyzed by fuzzy c-means clustering methods. Clustering should help to discover groups of glomeruli that are similary activated according to their response profiles across the odorants. To investigate the significance of the achieved fuzzy partitions we developed and applied a novel validity approach based on cluster stability. Our results show certain level of glomerular clustering in the olfactory bulb and indicate that exist a main chemo-topic subdivision of the glomerular layer in few macro-area which are rather specific to particular functional groups of the volatile molecules.

JTD Keywords: Olfactory bulb, 2-deoxyglucose mapping, Olfactory coding, Cluster analysis, Cluster validity