Abstract
This article reports on a study on olive-fly infestation prediction using machine learning techniques. . The purpose of the work was, on the one hand, to make accurate predictions and, on the other, to verify whether the Bayesian network techniques are competitive with respect to classification trees. We have applied the techniques to a dataset and, in addition, performed a previous phase of variables selection to simplify the complexity of the classifiers. The results of the experiments show that Bayesians networks produce valid predictors, although improved definition of dependencies and refinement of the variables selection methods are required.
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del Sagrado, J., del Águila, I.M. (2007). Olive Fly Infestation Prediction Using Machine Learning Techniques. In: Borrajo, D., Castillo, L., Corchado, J.M. (eds) Current Topics in Artificial Intelligence. CAEPIA 2007. Lecture Notes in Computer Science(), vol 4788. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75271-4_24
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DOI: https://doi.org/10.1007/978-3-540-75271-4_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-75270-7
Online ISBN: 978-3-540-75271-4
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