Hier finden Sie wissenschaftliche Publikationen aus den Fraunhofer-Instituten.

Exploiting the structures of the U-matrix

: Lötsch, J.; Ultsch, A.


Villmann, T.:
Advances in Self-Organizing Maps and Learning Vector Quantization : Proceedings of the 10th International Workshop, WSOM 2014, Mittweida, Germany, July, 2-4, 2014
Cham: Springer International Publishing, 2014 (Advances in Intelligent Systems and Computing 295)
ISBN: 978-3-319-07694-2 (Print)
ISBN: 978-3-319-07695-9 (Online)
Workshop on Self- Organizing Maps (WSOM) <10, 2014, Mittweida>
Conference Paper
Fraunhofer IME ()

The U-matrix has become a standard visualization of self-organizing feature maps (SOM). Here we present the abstract U-matrix, which formalizes the structures on a U-matrix such that distance calculations between best-matching units w.r.t. the height structures of a U-matrix are precisely defined (U-cell distance). This enables the assessment of the topological correctness of the SOM and the implementation of clustering algorithms that take the structures seen on the U-matrix into account. A weighted Delaunay graph of the U-cell distances allows the calculation of a dendrogram corresponding to the structures of the U-matrix. The method is shown to detect and visualize meaningful cluster structures on difficult artificial and real-life data.