Data Mining in Agriculture, 2009
Springer Optimization and Its Applications Series, Vol. 34

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Language: English

Approximative price 52.74 €

In Print (Delivery period: 15 days).

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Data Mining in Agriculture
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274 p. · 15.5x23.5 cm · Paperback

Approximative price 52.74 €

Subject to availability at the publisher.

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Data mining in agriculture (Optimization & its applications, Vol. 34)
Publication date:
274 p. · 15.5x23.5 cm · Hardback

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®.

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.

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