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

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À propos

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.


  • Auteur(s)

    Alfredo Vellido, Karina Gibert, Cecilio Angulo, Jose David Martin Guerrero

  • Éditeur

    Springer

  • Distributeur

    Numilog

  • Date de parution

    27/04/2019

  • EAN

    9783030196424

  • Disponibilité

    Disponible

  • Action copier/coller

    Dans le cadre de la copie privée

  • Nb pages copiables

    1

  • Action imprimer

    Dans le cadre de la copie privée

  • Nb pages imprimables

    1

  • Partage

    Dans le cadre de la copie privée

  • Nb Partage

    6 appareils

  • Poids

    45 117 Ko

  • Diffuseur

    Numilog

  • Entrepôt

    Numilog

  • Support principal

    ebook (ePub)

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