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Advances in self-organizing maps, le...

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Advances in self-organizing maps, learning vector quantization, clustering and data visualizationproceedings of the 13th International Workshop, WSOM+ 2019, Barcelona, Spain, June 26-28, 2019 /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Advances in self-organizing maps, learning vector quantization, clustering and data visualizationedited by Alfredo Vellido ... [et al.].
Reminder of title:	proceedings of the 13th International Workshop, WSOM+ 2019, Barcelona, Spain, June 26-28, 2019 /
remainder title:	WSOM+ 2019
other author:	Vellido, Alfredo.
corporate name:
Published:	Cham :Springer International Publishing :2020.
Description:	xii, 342 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Neural networks (Computer science)
Online resource:	https://doi.org/10.1007/978-3-030-19642-4
ISBN:	9783030196424$q(electronic bk.)

Advances in self-organizing maps, learning vector quantization, clustering and data visualizationproceedings of the 13th International Workshop, WSOM+ 2019, Barcelona, Spain, June 26-28, 2019 /
Advances in self-organizing maps, learning vector quantization, clustering and data visualizationproceedings of the 13th International Workshop, WSOM+ 2019, Barcelona, Spain, June 26-28, 2019 /[electronic resource] :WSOM+ 2019edited by Alfredo Vellido ... [et al.]. - Cham :Springer International Publishing :2020. - xii, 342 p. :ill., digital ;24 cm. - Advances in intelligent systems and computing,v.9762194-5357 ;. - Advances in intelligent systems and computing ;176..

This book gathers papers presented at the 13th International Workshop on Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization (WSOM+), which was held in Barcelona, Spain, from the 26th to the 28th of June 2019. Since being founded in 1997, the conference has showcased the state of the art in unsupervised machine learning methods related to the successful and widely used self-organizing map (SOM) method, and extending its scope to clustering and data visualization. In this installment of the AISC series, the reader will find theoretical research on SOM, LVQ and related methods, as well as numerous applications to problems in fields ranging from business and engineering to the life sciences. Given the scope of its coverage, the book will be of interest to machine learning researchers and practitioners in general and, more specifically, to those looking for the latest developments in unsupervised learning and data visualization.

ISBN: 9783030196424$q(electronic bk.)

Standard No.: 10.1007/978-3-030-19642-4doiSubjects--Topical Terms:

181982
Neural networks (Computer science)

LC Class. No.: QA76.87

Dewey Class. No.: 006.32

Advances in self-organizing maps, learning vector quantization, clustering and data visualizationproceedings of the 13th International Workshop, WSOM+ 2019, Barcelona, Spain, June 26-28, 2019 /
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