C4.5: programs for machine learning
C4.5: programs for machine learning
Neural networks for pattern recognition
Neural networks for pattern recognition
Predictive data mining: a practical guide
Predictive data mining: a practical guide
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Machine Learning
SVMTorch: support vector machines for large-scale regression problems
The Journal of Machine Learning Research
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The human eye may present refractive errors as myopia, hypermetropia and astigmatism. This article presents the development of an Ensemble of Classifiers as part of a Refractive Errors Measurement System. The system analyses Hartmann-Shack images from human eyes in order to identify refractive errors, wich are associated to myopia, hypermetropia and astigmatism. The ensemble is composed by three different Machine Learning techniques: Artificial Neural Networks, Support Vector Machines and C4.5 algorithm and has been shown to be able to improve the performance achieved). The most relevant data of these images are extracted using Gabor wavelets transform. Machine learning techniques are then employed to carry out the image analysis.