Martijn van der Werff

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Clinical proteomics based on mass spectrometry has gained tremendous visibility in the scientific and clinical community. Machine learning methods are keys for efficient processing of the complex data. One major class are prototype based algorithms. Prototype based vector quantizers or classifiers are intuitive approaches realizing the principle of(More)
We present a general framework for association learning in self-organizing maps (SOMs), which can be specified for the utilization for supervised fuzzy classification. In this way, we obtain a prototype based fuzzy classification model (FLSOM), which can be easily interpreted and visualized due to the fundamental properties of SOMs. Moreover, the provided(More)
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