Carregant...
Carregant...

Vés al contingut (premeu Retorn)

SVM-based feature selection to optimize sensitivity–specificity balance applied to weaning

Autor
Garde, A.; Voss, A.; Caminal, P.; Benito, S.; Giraldo, B.
Tipus d'activitat
Article en revista
Revista
Computers in biology and medicine
Data de publicació
2013
Volum
43
Número
5
Pàgina inicial
533
Pàgina final
540
DOI
https://doi.org/10.1016/j.compbiomed.2013.01.014 Obrir en finestra nova
Repositori
http://hdl.handle.net/2117/18985 Obrir en finestra nova
URL
http://www.sciencedirect.com/science/article/pii/S0010482513000280 Obrir en finestra nova
Resum
Classification algorithms with unbalanced data sets tend to produce high predictive accuracy over the majority class, but poor predictive accuracy over the minority class. This problem is very common in biomedical data mining. This paper introduces a Support Vector Machine(SVM)-based optimized features election method, to select the most relevant features and maintain an accurate and well-balanced sensitivity–specificity result between unbalanced groups. A new metric called the balance index(B...
Citació
Garde, A. [et al.]. SVM-based feature selection to optimize sensitivity–specificity balance applied to weaning. "Computers in biology and medicine", 2013, vol. 43, p. 533-540.
Paraules clau
Support vectormachines Balance index Sensitivity–specificity balance Cardiorespiratory interaction Joint symbolicdynamics Feature selection Weaning procedure
Grup de recerca
B2SLab - Bioinformatics and Biomedical Signals Laboratory
BIOSPIN - Biomedical Signal Processing and Interpretation
CREB - Centre de Recerca en Enginyeria Biomedica

Participants