Visual Knowledge Discovery and Machine Learning (Intelligent Systems Reference Library (144))
Language: English
Published by Springer, 2018
Series: Book 115 of 188 - Intelligent Systems Reference Library
- Hardcover
- New

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- Title
- Visual Knowledge Discovery and Machine Learning (Intelligent Systems Reference Library (144))
- Author
- Kovalerchuk, Boris
- Publisher
- Springer
- Publication year
- 2018
- Condition
- New
- Book Type
- book
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 3319730398
- ISBN 13
- 9783319730394
- Series
- Book 115 of 188: Intelligent Systems Reference Library
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.
"Synopsis" may belong to another edition of this title.
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.
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Mispah books
Redhill, Surrey, United Kingdom
AbeBooks seller since April 15, 2021
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