Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization

The book "Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization" offers a comprehensive collection of current advancements in the fields of self-organizing maps (SOMs) and learning vector quantization (LVQ). It addresses both theoretical and practical aspects and highlights innovative approaches to utilizing parallel computing methods. The content is balanced, covering traditional application areas such as data analysis and visualization problems, while also discussing newer applications like trajectory clustering and the use of quantum computational approaches. This specialized book is aimed at researchers and practitioners in the field of data analysis and machine learning who wish to stay informed about the latest developments in unsupervised learning and data visualization.