Prototype-based fuzzy classification with local relevance for proteomics

In this paper, we extend soft nearest prototype classification by local metric learning and fuzzy classification. Thereby, the metric is determined according to the given classification task. This may be done separately for each prototype or class specific. We apply the method to cancer detection based on proteomic data.