Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Alexander Ylnner Choquenaira Florez"'
Autor:
Afonso Matheus Sousa Lima, Alexander Ylnner Choquenaira Florez, Alexis Iván Aspauza Lescano, João Victor De Oliveira Novaes, Natalia De Fatima Martins, Caetano Traina Junior, Elaine Parros Machado de Sousa, José Fernando Rodrigues Junior, Robson Leonardo Ferreira Cordeiro
Publikováno v:
Journal of Information and Data Management. 11
Data analysis is increasingly being used as an unbiased and accurate way to evaluate many aspects of society and their evolution over the years. This article presents an analysis of student’s characteristics, between 2012 and 2017, in the most impo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::26952cc4ad1cf894653bbe4b29b54443
https://doi.org/10.5753/jidm.2020.2023
https://doi.org/10.5753/jidm.2020.2023
Autor:
Alexander Ylnner Choquenaira Florez, Patricia Batista Franco, Diana Carolina Roca Arroyo, Braulio Valentin Sanchez Vinces, Josimar Edinson Chire Saire
Publikováno v:
2020 International Conference of Digital Transformation and Innovation Technology (Incodtrin).
This work brings together some of the most common machine learning (ML) algorithms, and the objective is to make a comparison at the level of obtained results from a set of unbalanced data. This dataset is composed of almost 17 thousand observations
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dfcdbd1acc2773c6cfb35123d13e7462
https://doi.org/10.1109/incodtrin51881.2020.00027
https://doi.org/10.1109/incodtrin51881.2020.00027
Autor:
Daniela Fernanda Milón Flores, Alexander Ylnner Choquenaira Florez, Diana Carolina Roca Arroyo, Liang Zhao, Roseli A F Romero
Publikováno v:
Applications of Computational Intelligence ISBN: 9783030697730
Echo State Network (ESN) has been widely studied and applied to many problems due to the simplicity of its training phase. This is because since in this network only the output weights are trained, avoiding to deal with the gradient’s vanishing pro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::804466ecf9be90339f2136d95b7cd458
https://doi.org/10.1109/colcaci50549.2020.9248714
https://doi.org/10.1109/colcaci50549.2020.9248714
Autor:
Sihem Amer-Yahia, Alexander Ylnner Choquenaira Florez, José Fernando Rodrigues Junior, Lucas C. Scabora
Publikováno v:
2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS)
2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS), Jul 2020, Rochester, France. pp.597-602, ⟨10.1109/CBMS49503.2020.00118⟩
CBMS
2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS), Jul 2020, Rochester, France. pp.597-602, ⟨10.1109/CBMS49503.2020.00118⟩
CBMS
Methods based on neural networks have become more and more attractive in the medical domain as Deep Learning frameworks mature and popularize. One application in this context refers to the use of recurrent networks to predict the most probable clinic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::af184db68305376c9209b7810a6a3989
https://hal.archives-ouvertes.fr/hal-02972541
https://hal.archives-ouvertes.fr/hal-02972541
