Visual Knowledge Discovery and Machine Learning

Boris Kovalerchuk

ISBN 10: 3319892304 ISBN 13: 9783319892306
Published by Springer, 2019
New Taschenbuch

From preigu, Osnabrück, Germany Seller rating 5 out of 5 stars 5-star rating, Learn more about seller ratings

AbeBooks Seller since 5 August 2024

This specific item is no longer available.

About this Item

Description:

Visual Knowledge Discovery and Machine Learning | Boris Kovalerchuk | Taschenbuch | xxi | Englisch | 2019 | Springer | EAN 9783319892306 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Seller Inventory # 115141084

Report this item

Synopsis:

This book combines the advantages of high-dimensional data visualization and machine learning in the context of identifying complex n-D data patterns. It vastly expands the class of reversible lossless 2-D and 3-D visualization methods, which preserve the n-D information. This class of visual representations, called the General Lines Coordinates (GLCs), is accompanied by a set of algorithms for n-D data classification, clustering, dimension reduction, and Pareto optimization. The mathematical and theoretical analyses and methodology of GLC are included, and the usefulness of this new approach is demonstrated in multiple case studies. These include the Challenger disaster, world hunger data, health monitoring, image processing, text classification, market forecasts for a currency exchange rate, computer-aided medical diagnostics, and others. As such, the book offers a unique resource for students, researchers, and practitioners in the emerging field of Data Science.

From the Back Cover:

This book combines the advantages of high-dimensional data visualization and machine learning in the context of identifying complex n-D data patterns. It vastly expands the class of reversible lossless 2-D and 3-D visualization methods, which preserve the n-D information. This class of visual representations, called the General Lines Coordinates (GLCs), is accompanied by a set of algorithms for n-D data classification, clustering, dimension reduction, and Pareto optimization. The mathematical and theoretical analyses and methodology of GLC are included, and the usefulness of this new approach is demonstrated in multiple case studies. These include the Challenger disaster, world hunger data, health monitoring, image processing, text classification, market forecasts for a currency exchange rate, computer-aided medical diagnostics, and others. As such, the book offers a unique resource for students, researchers, and practitioners in the emerging field of Data Science.

"About this title" may belong to another edition of this title.

Bibliographic Details

Title: Visual Knowledge Discovery and Machine ...
Publisher: Springer
Publication Date: 2019
Binding: Taschenbuch
Condition: Neu

Top Search Results from the AbeBooks Marketplace

There are 1 more copies of this book

View all search results for this book