Data Mining in Agriculture represents a comprehensive effort to provide graduate students and researchers with an analytical text on data mining techniques applied to agriculture and environmental related fields. This book presents both theoretical and practical insights with a focus on presenting the context of each data mining technique rather intuitively with ample concrete examples represented graphically and with algorithms written in Matlab(r). Examples and exercises with solutions are provided at the end of each chapter to facilitate the comprehension of the material. For each data mining technique described in the book variants and improvements of the basic algorithm are also given.
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Data Mining in Agriculture represents a comprehensive effort to provide graduate students and researchers with an analytical text on data mining techniques applied to agriculture and environmental related fields. This book presents both theoretical and practical insights with a focus on presenting the context of each data mining technique rather intuitively with ample concrete examples represented graphically and with algorithms written in Matlab(r). Examples and exercises with solutions are provided at the end of each chapter to facilitate the comprehension of the material. For each data mining technique described in the book variants and improvements of the basic algorithm are also given.
Imprint | Springer-Verlag New York |
Country of origin | United States |
Series | Springer Optimization and Its Applications, 34 |
Release date | August 2009 |
Availability | Expected to ship within 12 - 17 working days |
First published | 2009 |
Authors | Antonio Mucherino, Petraq Papajorgji, Panos M. Pardalos |
Dimensions | 235 x 155 x 21mm (L x W x T) |
Format | Hardcover |
Pages | 274 |
Edition | 2009 ed. |
ISBN-13 | 978-0-387-88614-5 |
Barcode | 9780387886145 |
Categories | |
LSN | 0-387-88614-1 |