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A Markov random field model for combining optimum-path forest classifiers using decision graphs and game strategy approach
(2011-11-28)
The research on multiple classifiers systems includes the creation of an ensemble of classifiers and the proper combination of the decisions. In order to combine the decisions given by classifiers, methods related to fixed ...
A Markov random field model for combining optimum-path forest classifiers using decision graphs and game strategy approach
(2011-11-28)
The research on multiple classifiers systems includes the creation of an ensemble of classifiers and the proper combination of the decisions. In order to combine the decisions given by classifiers, methods related to fixed ...
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 ...
A Markov Random Field Model for Combining Optimum-Path Forest Classifiers Using Decision Graphs and Game Strategy Approach
(Springer, 2011-01-01)
The research on multiple classifiers systems includes the creation of an ensemble of classifiers and the proper combination of the decisions. In order to combine the decisions given by classifiers, methods related to fixed ...
Objective measures ensemble in associative classifiers
(2020-01-01)
Associative classifiers (ACs) are predictive models built based on association rules (ARs). Model construction occurs in steps, one of them aimed at sorting and pruning a set of rules. Regarding ordering, usually objective ...
Objective Measures Ensemble in Associative Classifiers
(Scitepress, 2020-01-01)
Associative classifiers (ACs) are predictive models built based on association rules (ARs). Model construction occurs in steps, one of them aimed at sorting and pruning a set of rules. Regarding ordering, usually objective ...
Classifiers in Paresi-Haliti (Arawak)
(Universidade Federal do Pará, 2016)
Confidence based multiple classifier fusion in speaker verification
(ELSEVIER, 2008-05-01)
A novel framework that applies Bayes-based confidence measure for multiple classifier system fusion is proposed. Compared with ordinary Bayesian fusion, the presented approach can lead to reductions as high as 37% and 35% ...
Detecção de intrusões através da seleção dinâmica de classificador baseada em redes de conselhos
(Universidade Federal de Santa MariaBrasilCiência da ComputaçãoUFSMPrograma de Pós-Graduação em Ciência da ComputaçãoCentro de Tecnologia, 2018-02-01)
Intrusion Detection Systems are common used for information analysis, that are collected
from computer networks and computer systems. Through the use of techniques such
as data classification, it is possible to identify ...