Métodos no paramétricos para la comparación de curvas ROC con covariables
A. Fanjul Hevia, W. González Manteiga, J. C. Pardo-Fernández
La curva ROC (del inglés, Receiver Operating Characteristic curve) es una herramienta estadística basada en las nociones de sensibilidad y especificidad que se utiliza para evaluar la capacidad discriminativa de un problema de clasificación. Cuando hay más de un método de clasificación se pueden utilizar estas curvas para comparar su comportamiento mediante la comparación de sus respectivas curvas ROC.
Por otra parte, hay ocasiones en las que la existencia de covariables afecta la capacidad de clasificación de estos métodos, por lo que hay que tenerlas en consideración. La curva ROC condicionada o la curva ROC ajustadas son dos formas de incluir esa información en el estudio.
En este trabajo se analiza, mediante contrastes no paramétricos, la relación de las curvas ROC condicionada, ajustada y la conjunta para comparar distintos métodos de clasificación y al mismo tiempo tener en cuenta la información de las covariables.
Keywords: Contrastes de hipótesis, covariables, curvas AROC, curvas ROC
Scheduled
GT18 Non-parametric statistics I. Non-parametric hypothesis tests
June 9, 2022 10:10 AM
A15
Other papers in the same session
A. Lago Balseiro, J. de Uña Álvarez, J. C. Pardo-Fernández
M. Conde-Amboage, I. Van Keilegom, W. González-Manteiga
E. García Portugués
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