Olive Fly Infestation Prediction Using Machine Learning Techniques

Authors:
José Sagrado;Isabel María Águila
Affiliations:
Dpt. of Languages and Computation, University of Almería, 04120 Almería, Spain;Dpt. of Languages and Computation, University of Almería, 04120 Almería, Spain
Venue:
Current Topics in Artificial Intelligence
Year:
2007

Citing 5
Cited 1

Bayesian Network Classifiers

Machine Learning - Special issue on learning with probabilistic representations
Bayesian Networks and Decision Graphs

Bayesian Networks and Decision Graphs
Pattern Classification (2nd Edition)

Pattern Classification (2nd Edition)
A Bayesian belief network for IT implementation decision support

Decision Support Systems
Software maintenance project delays prediction using Bayesian Networks

Expert Systems with Applications: An International Journal

SAIFA: A web-based system for Integrated Production of olive cultivation

Computers and Electronics in Agriculture

Quantified Score

Hi-index	0.00

Visualization

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.