{"id":16348,"date":"2024-04-07T21:01:50","date_gmt":"2024-04-07T21:01:50","guid":{"rendered":"https:\/\/promoguy.nl\/?post_type=entity&p=16348"},"modified":"2024-04-07T21:01:50","modified_gmt":"2024-04-07T21:01:50","slug":"specificity","status":"publish","type":"entity","link":"https:\/\/promoguy.nl\/es\/blog\/vocabulary\/specificity\/","title":{"rendered":"especificidad"},"content":{"rendered":"<p>La sensibilidad y la especificidad son medidas estad\u00edsticas del rendimiento de una prueba de clasificaci\u00f3n binaria, tambi\u00e9n conocida en estad\u00edstica como funci\u00f3n de clasificaci\u00f3n. La sensibilidad (tambi\u00e9n llamada tasa de verdaderos positivos, o tasa de recuerdo en algunos campos) mide la proporci\u00f3n de verdaderos positivos que se identifican correctamente como tales (por ejemplo, el porcentaje de personas enfermas a las que se identifica correctamente como portadoras de la enfermedad), y es complementaria de la tasa de falsos negativos. La especificidad (a veces denominada tasa de verdaderos negativos) mide la proporci\u00f3n de negativos que se identifican correctamente como tales (por ejemplo, el porcentaje de personas sanas que se identifican correctamente como no enfermas), y es complementaria de la tasa de falsos positivos. Un predictor perfecto se describir\u00eda como 100% sensible (por ejemplo, todos los enfermos son identificados como enfermos) y 100% espec\u00edfico (por ejemplo, todos los sanos no son identificados como enfermos); sin embargo, te\u00f3ricamente cualquier predictor poseer\u00e1 un l\u00edmite de error m\u00ednimo conocido como tasa de error de Bayes. En cualquier prueba, suele haber un equilibrio entre las medidas. Por ejemplo, en un aeropuerto en el que se buscan amenazas potenciales para la seguridad, los esc\u00e1neres pueden estar configurados para detectar objetos de bajo riesgo, como hebillas de cintur\u00f3n y llaves (baja especificidad), con el fin de reducir el riesgo de pasar por alto objetos que s\u00ed suponen una amenaza para el avi\u00f3n y sus pasajeros (alta sensibilidad). Este equilibrio puede representarse gr\u00e1ficamente mediante una curva receiver operating characteristic.<\/p>","protected":false},"excerpt":{"rendered":"<p>Sensitivity and specificity are statistical measures of the performance of a binary classification test, also known in statistics as classification function. Sensitivity (also called the true positive rate, or the recall rate in some fields) measures the proportion of actual positives which are correctly identified as such (e.g., the percentage of sick people who are [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"","ping_status":"closed","template":"","meta":{"_acf_changed":false,"wl_entities_gutenberg":"","footnotes":""},"categories":[],"wl_entity_type":[39],"class_list":["post-16348","entity","type-entity","status-publish","hentry","wl_entity_type-thing"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.8 (Yoast SEO v27.8) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>specificity - Promoguy Digital Marketing Agency<\/title>\n<meta name=\"robots\" content=\"noindex, follow\" \/>\n<meta property=\"og:locale\" content=\"es_ES\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"specificity\" \/>\n<meta property=\"og:description\" content=\"Sensitivity and specificity are statistical measures of the performance of a binary classification test, also known in statistics as classification function. 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