By Panos M. Pardalos, Antonio Mucherino, Petraq J. Papajorgji
Data Mining in Agriculture represents a finished attempt to supply graduate scholars and researchers with an analytical textual content on information mining innovations utilized to agriculture and environmental comparable fields. This ebook provides either theoretical and useful insights with a spotlight on providing the context of every information mining method relatively intuitively with considerable concrete examples represented graphically and with algorithms written in MATLAB®.
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Extra info for Data Mining in Agriculture (Springer Optimization and Its Applications)
For this reason, experiments in MATLAB r and/or applications of freeware software for data mining are discussed in each chapter. 6 General structure of the book 21 them by using little code. Codes in MATLAB are provided for both techniques. They are very simple and may not work in some kinds of situations. Our aim is to keep the simplicity, however the reader could even modify such codes for solving particular problems. Artificial neural network and support vector machines are much more complex.
Codes in MATLAB are provided for both techniques. They are very simple and may not work in some kinds of situations. Our aim is to keep the simplicity, however the reader could even modify such codes for solving particular problems. Artificial neural network and support vector machines are much more complex. Therefore, various software implementing such techniques are presented and examples on how to use them are discussed. At the end of each chapter, a section devoted to exercises is given. The solutions of such exercises can be found in Chapter 10.
The parallel version of some of the data mining techniques discussed in the book are given. This book provides two appendices. Appendix A gives some details about the MATLAB environment. The reader who is interested in MATLAB can also find a lot of textbooks in literature. Therefore, only the basic concepts needed for understanding the several examples in MATLAB given in this book are discussed. Appendix B presents an entire application in C programming language. The implemented algorithm is the k-means algorithm.
Data Mining in Agriculture (Springer Optimization and Its Applications) by Panos M. Pardalos, Antonio Mucherino, Petraq J. Papajorgji