Generalized matrix learning vector quantizer for the analysis of spectral data
نویسندگان
چکیده
The analysis of spectral data constitutes new challenges for machine learning algorithms due to the functional nature of the data. Special attention is given to the used metric in such analysis. Recently a prototype based algorithm has been proposed which allows the integration of a full adaptive matrix in the metric. In this contribution we analyse this approach with respect to band matrices and its usage for the analysis of functional spectral data. The approach is tested on satellite data and data taken from food chemistry.
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