Zobrazeno 1 - 6
of 6
pro vyhledávání: '"João C. Xavier-Junior"'
Publikováno v:
Information, Vol 9, Iss 11, p 268 (2018)
Metaheuristic algorithms have been applied to a wide range of global optimization problems. Basically, these techniques can be applied to problems in which a good solution must be found, providing imperfect or incomplete knowledge about the optimal s
Externí odkaz:
https://doaj.org/article/f847128a3c2a41989a22f96f9013b51b
Publikováno v:
Brazilian Journal of Development. 6:87089-87112
Prever antecipadamente despesas possibilita que as instituicoes consigam alocar recursos em acoes e projetos de forma mais planejada, reduzam o trabalho operacional para realocacao de recursos nao utilizados e reservados para pagamento de despesas qu
Autor:
Alexandre César Muniz de Oliveira, João C. Xavier Junior, Anne M. P. Canuto, Antonino Feitosa Neto
Publikováno v:
BRACIS
This work performs an empirical study on Automated Machine Learning (Auto-ML) systems for automatically selecting the best Classifier Ensembles and their hyper-parameter settings or by only selecting the hyper-parameter of a predetermined Classifier
Autor:
Luis Marcos G. Gonçalves, Michael Fairhurst, Antonino Feitosa Neto, Anne M. P. Canuto, João C. Xavier Junior, Fernando Pintro
Publikováno v:
International Journal of Hybrid Intelligent Systems. 8:143-154
The main aim of biometric-based identification systems is to automatically recognize individuals based on their physiological and/or behavioural characteristics such as fingerprint, face, hand-geometry, among others. These systems offer several advan
Publikováno v:
International Journal of Hybrid Intelligent Systems. 3:147-158
There are two main approaches to combine the output of classifiers within a multi-classifier system (MCS), which are: combination-based and selection-based methods. In selection-based methods, only one classifier is needed to correctly classify the i
Autor:
Cephas A. S. Barreto, Arthur Costa Gorgonio, Joao C. Xavier-Junior, Anne Magaly De Paula Canuto
Publikováno v:
IEEE Access, Vol 10, Pp 43535-43551 (2022)
Semi-supervised learning (SSL) is a machine learning approach that integrates supervised and unsupervised learning mechanisms. This integration may be done in different ways and one possibility is to use a wrapper-based strategy. The main aim of a wr
Externí odkaz:
https://doaj.org/article/2b5bdc283e6144f5b0465c9fcd0b852f