Visual interpretation of self organizing maps
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2010-10-23
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KITANI, E. C.
DEL MORAL HERNANDEZ, E.
Carlos E. Thomaz
DA SILVA, L. A.
DEL MORAL HERNANDEZ, E.
Carlos E. Thomaz
DA SILVA, L. A.
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Proceedings - 2010 11th Brazilian Symposium on Neural Networks, SBRN 2010
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KITANI, E. C.; DEL MORAL HERNANDEZ, E.; THOMAZ, C. E.; DA SILVA, L. A. Visual interpretation of self organizing maps. Proceedings - 2010 11th Brazilian Symposium on Neural Networks, SBRN 2010, p. 37-42, Oct. 2010.
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The design and test of a two-stage PCA+SOM methodology targeting applications on images database are presented and the result of the SOM map is analyzed by reconstructing the prototypes (codebook) of the map in terms of concrete images in the input space. This visual analysis allows us to interpret which features were used by the SOM algorithm to create a self-organizing map. Several approaches in the SOM literature study the numbers of clusters captured by the algorithm; this research work views the production of tools that help us to know which features led to self-organization. To accomplish this task, a high dimensional, complex and controlled database formed by human face images has been used. The experimental demonstration of the methodology is made through the analysis of a face database. Despite the complexity of having computations with images of faces, they are easily identified and understood by humans. © 2010 IEEE.