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Data Mining in Agriculture

Data Mining in Agriculture
Catalogue Information
Field name Details
Dewey Class 519.6
Title Data Mining in Agriculture ([Ebook]) / by Antonio Mucherino, Petraq J. Papajorgji, Panos M. Pardalos.
Author Mucherino, Antonio
Added Personal Name Papajorgji, Petraq J.
Pardalos, Panos M.
Other name(s) SpringerLink (Online service)
Publication New York, NY : Springer , 2009.
Physical Details XVIII, 274 pages : 92 illus. : online resource.
Series Springer Optimization and Its Applications 1931-6828 ; ; 34
ISBN 9780387886152
Summary Note 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.:
Contents note Introduction to Data Mining -- 2 Statistical Methods -- 3 Clustering by k-means -- 4 k-nearest Neighbor Classification -- 5 Artificial Neural Networks -- 6 Support Vector Machines -- 7 Biclustering -- 8 Validation -- 9 An Application in C -- 10 Data Mining in a Parallel Environment -- 11 Solutions of the Exercises -- A. Matlab Environment -- B. C programming language -- C. Message Passing Interface (MPI) -- D. Eigenvalues and Eigenvectors -- References.
System details note Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users).
Internet Site http://dx.doi.org/10.1007/978-0-387-88615-2
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