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Validation

In: Data Mining in Agriculture

Author

Listed:
  • Antonio Mucherino

    (University of Florida)

  • Petraq J. Papajorgji

    (University of Florida)

  • Panos M. Pardalos

    (University of Florida)

Abstract

This book presents details for some of the most frequently used data mining techniques in the field of agriculture.As pointed out in Chapter 1, data mining techniques can be mainly divided into clustering and classification techniques. Clustering techniques are used when there is not any previous knowledge about the data, and hence a partition in clusters grouping similar data is searched.When a training set is available, classification techniques can be applied. In such cases, the training set is exploited for classifying data of unknown classification. The training set can be exploited in two ways: it can be used directly for performing the classification, or it can be used for setting up the parameters of a model which fits the data.

Suggested Citation

  • Antonio Mucherino & Petraq J. Papajorgji & Panos M. Pardalos, 2009. "Validation," Springer Optimization and Its Applications, in: Data Mining in Agriculture, chapter 0, pages 161-172, Springer.
    • Handle: RePEc:spr:spochp:978-0-387-88615-2_8
    DOI: 10.1007/978-0-387-88615-2_8
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