Capacidad de clasificación de un marcador bivariante a través de restricciones lineales
S. Pérez Fernández, P. Martínez Camblor, N. Corral Blanco
La capacidad discriminativa de una variable continua (normalmente llamada marcador) para distinguir entre dos grupos se suele medir en términos de la sensibilidad y la especificidad. Cuando las reglas de clasificación se basan en un único punto de corte, las probabilidades anteriores se recogen en un gráfico denominado curva ROC (del inglés, _Receiver Operating Characteristic_).
Existen generalizaciones de la curva ROC para acomodar escenarios donde el uso de un único punto de corte está lejos de ser la regla de clasificación óptima. Un ejemplo es la llamada curva gROC, que considera dos umbrales.
En este trabajo se combina una reformulación de la definición de la curva ROC con la idea que subyace a la curva gROC, con el objetivo de construir regiones de clasificación interpretables que reporten la máxima sensibilidad para una especificidad fijada, en un escenario bivariante.
Keywords: curva gROC; reglas de clasificación; marcador bivariante; restricciones lineales
Scheduled
Multivariate Analysis II
June 8, 2022 5:20 PM
Cloister room
Other papers in the same session
C. Matrán Bea, D. Rodríguez Vítores
J. Camacho Páez, C. Díaz, P. Sánchez Rovira
J. J. Egozcue, V. Pawlowsky-Glahn
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