Mucherino A. Data Mining in Agriculture

Springer, 2009. — 274 p. — ISBN 0387886141.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.Introduction to Data Mining
Statistical Methods
Clustering by k-means
k-nearest Neighbor Classification
Artificial Neural Networks
Support Vector Machines
Biclustering
Validation
An Application in C
Data Mining in a Parallel Environment
Solutions of the Exercises
MatLAB Environment
C programming language
Message Passing Interface (MPI)
Eigenvalues and Eigenvectors