國立虎尾科技大學 |

Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization = Proceedings of the 13th International Workshop, WSOM+ 2019, Barcelona, Spain, June 26-28, 2019 /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization/ edited by Alfredo Vellido, Karina Gibert, Cecilio Angulo, José David Martín Guerrero.
其他題名:	Proceedings of the 13th International Workshop, WSOM+ 2019, Barcelona, Spain, June 26-28, 2019 /
其他作者:	Martín Guerrero, José David.
面頁冊數:	XII, 342 p. 161 illus., 113 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Artificial Intelligence. -
電子資源:	https://doi.org/10.1007/978-3-030-19642-4
ISBN:	9783030196424

Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization = Proceedings 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] :edited by Alfredo Vellido, Karina Gibert, Cecilio Angulo, José David Martín Guerrero. - 1st ed. 2020. - XII, 342 p. 161 illus., 113 illus. in color.online resource. - Advances in Intelligent Systems and Computing,9762194-5357 ;. - Advances in Intelligent Systems and Computing,335.

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

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

646849
Artificial Intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization = Proceedings of the 13th International Workshop, WSOM+ 2019, Barcelona, Spain, June 26-28, 2019 /
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