Titlebook: Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization; Dedicated to the Mem Jan Faigl,Madalina

Bernstein-test

,Sparse Weighted ,-Means for Groups of Mixed-Type Variables,le the data may be described by a large number of features, only a minority of them may be actually informative with regard to the structure. Furthermore, redundant features may also bias the clustering, whether one speaks of redundancy in the informative or the uninformative features. The present c

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Sciatica

,Neural Networks for Spatial Models,that takes into account the spatial dependence. Usual spatial econometric models are based on a neighbourhood matrix whose elements are linked to geographical distances. We propose to use distances between prototypes resulting from a neural classification instead. The results are at least as well as

Musculoskeletal

新字

Modification of the Classification-by-Component Predictor Using Dempster-Shafer-Theory,Dempster-Shafer-theory, which in the original approach was mentioned to be implicitly realized but not explained deeply. Thus, we redefine the CbC keeping the main aspects of positive and negative reasoning about detected components/features and relate this to the Demspster-Shafer-theory of evidence

异端邪说2

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反叛者

peritonitis

,GNG-based Clustering of Risk-aware Trajectories into Safe Corridors,pulated environments induces additional risk to people and properties on the ground. Risk-aware planning can mitigate the risk by preferring flying above low-risk areas such as rivers or brownfields. Finding such trajectories is computationally demanding, but they can be precomputed for areas that a

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