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

culinary

书目名称Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization影响因子(影响力)




书目名称Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization影响因子(影响力)学科排名




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书目名称Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization网络公开度学科排名




书目名称Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization被引频次




书目名称Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization被引频次学科排名




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书目名称Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization读者反馈学科排名

SLUMP

Curmudgeon

compel

巨头

https://doi.org/10.1007/978-1-4419-1123-0of empirical inference: the hierarchical agglomerative clustering and the computation of minimum enclosing balls. It produces .-nets whose cardinalities are smaller than those obtained with state-of-the-art methods.

recede

wangle

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.

bizarre

,Inferring ,-nets of Finite Sets in a RKHS,of empirical inference: the hierarchical agglomerative clustering and the computation of minimum enclosing balls. It produces .-nets whose cardinalities are smaller than those obtained with state-of-the-art methods.

错误

,Steps Forward to Quantum Learning Vector Quantization for Classification Learning on a Theoretical t quantum computing patterns and quantum hardware. For this purpose, we introduce a new computing pattern for prototype updates and possible measurement strategies in the quantum computing regime. Further, we consider numerical errors which are induced by the theoretical model and their impact on the learning process.

高贵领导

Jan Faigl,Madalina Olteanu,Jan DrchalProvides recent research in self-organizing maps, learning vector quantization, clustering, and data visualization.Presents computational aspects and applications for data mining and visualization.Con