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Data Mining in Agriculture: Springer Optimization and Its Applications, cartea 34

Autor Antonio Mucherino, Petraq Papajorgji, Panos M. Pardalos
en Limba Engleză Paperback – 25 feb 2012
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®. 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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Specificații

ISBN-13: 9781461429357
ISBN-10: 1461429358
Pagini: 292
Ilustrații: XVIII, 274 p. 92 illus.
Dimensiuni: 155 x 235 x 15 mm
Greutate: 0.41 kg
Ediția:2009
Editura: Springer
Colecția Springer
Seria Springer Optimization and Its Applications

Locul publicării:New York, NY, United States

Public țintă

Research

Cuprins

to Data Mining.- Statistical Based Approaches.- Clustering by -means.- -Nearest Neighbor Classification.- Artificial Neural Networks.- Support Vector Machines.- Biclustering.- Validation.- Data Mining in a Parallel Environment.- Solutions to Exercises.

Recenzii

From the reviews:
“This book covers several topics in data mining within the context of agriculture. … Every problem at the end of each chapter is provided with solutions … . who are looking for a first step into the field of data mining in agriculture may appreciate this broad nature … . Students interested in a hands-on approach using MATLAB may also find the book useful due to the sample solutions provided.” (R. Wan, Journal of the Operational Research Society, Vol. 61, 2010)
“The book … presents in a comprehensive way most up-to-date data mining techniques and their application to problems from agriculture domain. … Researchers, practitioners and students will find the book very useful … . Researchers will find in the book not only a good reference and a compendium of most important techniques but also an ‘all in one place’ analysis of most important data mining techniques … . Teachers can use the book for data mining subjects in undergraduate and graduate studies … .”­­­ (Fatos Xhafa, Journal of Global Optimization, Vol. 48, 2010)

Textul de pe ultima copertă

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®.
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.
Also by P.J. Papajorgji and P.M. Pardalos: Advances in Modeling Agricultural Systems, 'Springer Optimization and its Applications' vol. 25, ©2009.

Caracteristici

First textbook in data mining in agriculture Presentation suitable for students, researchers, and professionals, in the classroom or as a self-study Explores examples in agriculture/environmental fields Provides Matlab codes to illustrate examples Includes numerous exercises and some solutions