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Improving the accuracy of the optimum-path forest supervised classifier for large datasets
(2010-12-15)
In this work, a new approach for supervised pattern recognition is presented which improves the learning algorithm of the Optimum-Path Forest classifier (OPF), centered on detection and elimination of outliers in the ...
Improving the accuracy of the optimum-path forest supervised classifier for large datasets
(2010-12-15)
In this work, a new approach for supervised pattern recognition is presented which improves the learning algorithm of the Optimum-Path Forest classifier (OPF), centered on detection and elimination of outliers in the ...
Spoken emotion recognition using hierarchical classifiers
(Elsevier, 2011-07)
The recognition of the emotional state of speakers is a multi-disciplinary research area that has received great interest over the last years. One of the most important goals is to improve the voice-based human-machine ...
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 ...
On-line linear combination of classifiers based on incremental information in speaker verification
(ELECTRONICS TELECOMMUNICATIONS RESEARCH INST, 2010)
A novel multiclassifier system (MCS) strategy is proposed and applied to a text-dependent speaker verification task. The presented scheme optimizes the linear combination of classifiers on an on-line basis. In contrast to ...
Rank Aggregation for Pattern Classifier Selection in Remote Sensing Images
(Institute of Electrical and Electronics Engineers (IEEE), 2014-04-01)
In the past few years, segmentation and classification techniques have become a cornerstone of many successful remote sensing algorithms aiming at delineating geographic target objects. One common strategy relies on using ...