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

Alfredo Vellido, Cecilio Angulo, José David Martín Guerrero, Karina Gibert, 2019
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The book "Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization" brings together contributions presented at the 13th International Workshop on Self-Organizing Maps, Learning Vector Quantization, Clustering, and Data Visualization (WSOM+). This event took place from June 26 to 28, 2019, in Barcelona, Spain. Since its inception in 1997, the conference has highlighted the current state of the art in unsupervised machine learning, particularly the widely used method of self-organizing maps (SOM), and has expanded its application to clustering and data visualization. In this volume of the AISC series, readers will find theoretical research on SOM, LVQ, and related methods, as well as numerous applications across various fields, including business, engineering, and life sciences. The book is aimed at researchers and practitioners in the field of machine learning, especially those interested in the latest developments in unsupervised learning and data visualization.

Key specifications

topic
Mathematics & Natural Sciences
Subtopic
Computer science
Author
Alfredo VellidoCecilio AnguloJosé David Martín GuerreroKarina Gibert
Year
2019
Number of pages
342
Book cover
Paperback

General information

Item number
56067570
Publisher
Springer
Category
Reference books
Release date
11.3.2025

Book properties

topic
Mathematics & Natural Sciences
Subtopic
Computer science
Author
Alfredo VellidoCecilio AnguloJosé David Martín GuerreroKarina Gibert
Year
2019
Number of pages
342
Book cover
Paperback

Voluntary climate contribution

CO₂ emissions
0.25 kg
Climate contribution
CHF 0.11

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