Udo Seiffert

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Multidimensional Scaling (MDS) is a powerful dimension reduction technique for embedding high-dimensional data into a low-dimensional target space. Thereby, the distance relationships in the source are reconstructed in the target space as best as possible according to a given embedding criterion. Here, a new stress function with intuitive properties and a(More)
A correlation-based similarity measure is derived for generalized relevance learning vector quantization (GRLVQ). The resulting GRLVQ-C classifier makes Pearson correlation available in a classification cost framework where data prototypes and global attribute weighting terms are adapted into directions of minimum cost function values. In contrast to the(More)
In this work we introduce a method for visualization of fuzzy label information obtained from prototype based fuzzy labeled self-organizing map (FLSOM) for fuzzy classification. FLSOM returns vectors of fuzyy class labels for the prototypes containing class simlarity information. This information is used for apropriate visualization by an adequate,(More)
BACKGROUND Micro- and macroarray technologies help acquire thousands of gene expression patterns covering important biological processes during plant ontogeny. Particularly, faithful visualization methods are beneficial for revealing interesting gene expression patterns and functional relationships of coexpressed genes. Such screening helps to gain deeper(More)