DocumentCode :
2029705
Title :
Clustering by SOM (self-organising maps), MST (minimal spanning tree) and MCP (modified counter-propagation)
Author :
Obu-Cann, K. ; Iwamoto, K. ; Tokutaka, H. ; Fujimura, K.
Author_Institution :
Dept. of Electr. & Electron. Eng., Tottori Univ., Japan
Volume :
3
fYear :
1999
fDate :
1999
Firstpage :
986
Abstract :
Evaluation of the cluster classification generated by a SOM is usually done by human eye. Due to the qualitative nature of this experiment, the evaluator may either overestimate or underestimate the number of clusters formed on the map. With this approach, the exact number of clusters generated by the map cannot be confirmed because of the misinterpretation of the grey-level expression. This paper presents the use of MSTs and MCP in cluster classification and reports on the application of a SOM to the chemical analysis of alloys
Keywords :
alloys; backpropagation; chemical analysis; chemistry computing; minimisation; pattern classification; pattern clustering; self-organising feature maps; trees (mathematics); alloys; chemical analysis; cluster classification; cluster estimation; grey-level expression misinterpretation; minimal spanning tree; modified counter-propagation; qualitative evaluation; self-organising maps; Chemical analysis; Counting circuits; Electrons; Humans; Kinetic energy; Laboratories; Lattices; Multidimensional systems; Spectroscopy; X-ray scattering;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Information Processing, 1999. Proceedings. ICONIP '99. 6th International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-5871-6
Type :
conf
DOI :
10.1109/ICONIP.1999.844670
Filename :
844670
Link To Document :
بازگشت