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Improving accuracy and speed of optimum-path forest classifier using combination of disjoint training subsets
(2011-09-26)
The Optimum-Path Forest (OPF) classifier is a recent and promising method for pattern recognition, with a fast training algorithm and good accuracy results. Therefore, the investigation of a combining method for this kind ...
Improving accuracy and speed of optimum-path forest classifier using combination of disjoint training subsets
(2011-09-26)
The Optimum-Path Forest (OPF) classifier is a recent and promising method for pattern recognition, with a fast training algorithm and good accuracy results. Therefore, the investigation of a combining method for this kind ...
On semi-supervised learning
(Springer, 2020-12)
Major efforts have been made, mostly in the machine learning literature, to construct good predictors combining unlabelled and labelled data. These methods are known as semi-supervised. They deal with the problem of how ...
Improving Accuracy and Speed of Optimum-Path Forest Classifier Using Combination of Disjoint Training Subsets
(Springer, 2011-01-01)
The Optimum-Path Forest (OPF) classifier is a recent and promising method for pattern recognition, with a fast training algorithm and good accuracy results. Therefore, the investigation of a combining method for this kind ...
Training small producers in Good Manufacturing Practices for the development of goat milk cheese
(Sociedade Brasileira de Ciência e Tecnologia de Alimentos, 2018-01)
Training in Good Manufacturing Practices enhances quality during food processing. This paper evaluates GMP training aimed at improving the chemical, sensory and microbiological quality of goat milk cheese. We worked with ...