Title: Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization (eng)
Publisher: Springer
Publication Date: 2022
Language: English
ISBN 10: 3031154436
ISBN 13: 9783031154430
Binding: Soft cover
Condition: new
Weight: 0.22 kilograms

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Synopsis

In this collection, the reader can ﬁnd recent advancements in self-organizing maps (SOMs) and learning vector quantization (LVQ), including progressive ideas on exploiting features of parallel computing. The collection is balanced in presenting novel theoretical contributions with applied results in traditional ﬁelds of SOMs, such as visualization problems and data analysis. Besides, the collection further includes less traditional deployments in trajectory clustering and recent results on exploiting quantum computation. The presented book is worth interest to data analysis and machine learning researchers and practitioners, speciﬁcally those interested in being updated with current developments in unsupervised learning, data visualization, and self-organization.

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