Self-organizing maps and SVD

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	Similar Articles Articles by Jiri Dvorsky

18th International Conference on Database and Expert Systems Applications (DEXA 2007)

Regensburg, Germany

September 03-September 07

ISBN: 0-7695-2932-1

	ASCII Text	x
	Jiri Dvorsky, "Self-organizing maps and SVD," Database and Expert Systems Applications, International Workshop on, pp. 143-147, 18th International Conference on Database and Expert Systems Applications (DEXA 2007), 2007.

	BibTex	x
	@article{ 10.1109/DEXA.2007.86, author = {Jiri Dvorsky}, title = {Self-organizing maps and SVD}, journal ={Database and Expert Systems Applications, International Workshop on}, volume = {0}, year = {2007}, issn = {1529-4188}, pages = {143-147}, doi = {http://doi.ieeecomputersociety.org/10.1109/DEXA.2007.86}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Database and Expert Systems Applications, International Workshop on TI - Self-organizing maps and SVD SN - 1529-4188 SP143 EP147 A1 - Jiri Dvorsky, PY - 2007 KW - null VL - 0 JA - Database and Expert Systems Applications, International Workshop on ER -

Jiri Dvorsky, Technical University of Ostrava, Czech Republic

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/DEXA.2007.86

Mean square error is usual method to measure quality of self-organizing map (SOM). MSE brings good theoretical description about learning process, but its rather hard to decide what MSE is small enough, or when learning should be stoped. A new technique for measurement of quality of SOM using singular value decomposition will be presented in this paper.

Citation:

Jiri Dvorsky, "Self-organizing maps and SVD," dexa, pp.143-147, 18th International Conference on Database and Expert Systems Applications (DEXA 2007), 2007

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