Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Carine A. Dantas"'
Publikováno v:
2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1be26bfe1d5b7eaa1f36268382c0bf3e
https://doi.org/10.1109/icmla55696.2022.00144
https://doi.org/10.1109/icmla55696.2022.00144
Autor:
Kelly Costa De Almeida, Carine P.m. Dantas Tostes, Claudia Martins Foly, Vinicius D Avila Bitencourt Pascoal, Aislan Cristina R. F. Pascoal
Publikováno v:
Anais do II Congresso Brasileiro de Bioquímica Humana On-line.
INTRODUÇÃO: Os parâmetros bioquímicos dos animais utilizados em experimentação podem variar de acordo com a linhagem e matrizes fundadoras. Tais parâmetros, são amplamente utilizados na análise dos experimentos e portanto se torna imprescind
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0bd506d53c00d0a51abe1335cdbe5098
https://doi.org/10.51161/conbraqui/6
https://doi.org/10.51161/conbraqui/6
Autor:
Carolina Vieira Alves Lutterbach De Carvalho, Kelly Costa De Almeida, Carine P.m. Dantas Tostes, Gustavo Manso Fernandes, Aislan Cristina Rheder Fagundes Pascoal
Publikováno v:
Anais do II Congresso Brasileiro de Hematologia Clínico-laboratorial On-line.
INTRODUÇÃO: De acordo com a Sociedade Brasileira de Diabetes 2019-2020, o acompanhamento da glicose por meio da hemoglobina glicada é um importante preditor sobre o risco de complicações crônicas. Porém, a dosagem de HbA1c não apresenta resul
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c26fae5c40517ee57076e6290edd44cc
https://doi.org/10.51161/hematoclil/21
https://doi.org/10.51161/hematoclil/21
Publikováno v:
ICMLA
The aim of this paper is to investigate the use of Dynamic Feature Selection in classifier ensembles, aiming at improving its diversity and the performance of these systems. In order to do that, four dynamic feature selection techniques are proposed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7e1860e2809bf82ba6d81602e2230dee
https://doi.org/10.1109/icmla51294.2020.00089
https://doi.org/10.1109/icmla51294.2020.00089
Publikováno v:
BRACIS
Dynamic Feature Selection selects the best feature subset for each individual instance. In other words, each instance will be classified using its own feature subset. Recently, this idea has been combined with other dynamic approaches to create dynam
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8676015020bbf1dc9a951f11da9ac752
https://doi.org/10.1109/bracis.2019.00028
https://doi.org/10.1109/bracis.2019.00028
Publikováno v:
Computational Intelligence. 33:119-143
Ensemble systems are classification structures that apply a two-level decision-making process, in which the first level produces the outputs of the individual classifiers and the second level produces the output of the combination method final output
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8ed69df3de7258f9017895ddc494f0ec
https://doi.org/10.1111/coin.12090
https://doi.org/10.1111/coin.12090
Publikováno v:
BRACIS
In this paper, we propose a novel approach for dynamic feature selection to be applied in classifier ensembles. This method selects the best attribute subsets for an individual instance or a group of instances of an input dataset. Hence, each testing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6e1acfa5b7f102e7c800071356685522
https://doi.org/10.1109/bracis.2018.00087
https://doi.org/10.1109/bracis.2018.00087
Publikováno v:
IJCNN
A feature selection method has the objective of selecting the best feature subset that represents the entire dataset. The majority of these methods apply a static selection procedure, since it selects a feature subset and uses it throughout the class
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cd5fc3cb006c7a440f99f60a6c0a4db6
https://doi.org/10.1109/ijcnn.2018.8489162
https://doi.org/10.1109/ijcnn.2018.8489162
Publikováno v:
BRACIS
This paper presents a study about the impact of evaluation criteria and similarity measures in an unsupervisedbased feature selection (FS) method. The main aim of this paper is to assess the importance of these parameter in the analyzed FS method. Th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e0a7391218b0628bf46bc0afddb77d4e
https://doi.org/10.1109/bracis.2017.61
https://doi.org/10.1109/bracis.2017.61
Publikováno v:
IJCNN
Recently, the number of features in different problem domains has grown enormously. In order to select the best representation (attributes) for these problems, a deep knowledge of the problem domain is required. As this type of knowledge is not alway
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5318b7219231c3584a88059c75a1413d
https://doi.org/10.1109/ijcnn.2016.7727749
https://doi.org/10.1109/ijcnn.2016.7727749