Hierarchical PCA Using Tree-SOM for the Identification of Bacteria

Authors:
Stephan Simmuteit;Frank-Michael Schleif;Thomas Villmann;Markus Kostrzewa
Affiliations:
Dept. of Medicine, Univ. Leipzig, Leipzig, Germany 04107;Dept. of Medicine, Univ. Leipzig, Leipzig, Germany 04107;Dept. of MPI, Univ. of Appl. Sc. Mittweida, Mittweida, Germany 09648;Department of Bioanalytics, Bruker Daltonik GmbH, Bremen, Germany 28359
Venue:
WSOM '09 Proceedings of the 7th International Workshop on Advances in Self-Organizing Maps
Year:
2009

Citing 5
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Abstract

In this paper we present an extended version of Evolving Trees using Oja's rule. Evolving Trees are extensions of Self-Organizing Maps developed for hierarchical classification systems. Therefore they are well suited for taxonomic problems like the identification of bacteria. The paper focus on clustering and visualization of bacteria measurements. A modified variant of the Evolving Tree is developed and applied to obtain a hierarchical clustering. The method provides an inherent PCA analysis which is analyzed in combination with the tree based visualization. The obtained loadings support insights in the classification decision and can be used to identify features which are relevant for the cluster separation.