ROC curves as an aspect of classification
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F09%3A00038114" target="_blank" >RIV/00216224:14310/09:00038114 - isvavai.cz</a>
Výsledek na webu
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DOI - Digital Object Identifier
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Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
ROC curves as an aspect of classification
Popis výsledku v původním jazyce
Receiver Operating Characteristic (ROC) analysis has its origin in signal detection theory, but most of the current work occurs in the medical decision making community. Now, ROC curves have been widely used for evaluating the accuracy and discriminatingpower of a diagnostic test or statistical model. To derive a smooth estimate for the ROC curve, we use a kernel smoothing method. We estimate a distribution function by this process. It is well known now that kernel distribution estimators are not consistent when estimating a distribution near the finite end points of its support. This is due to boundary effects that occur in nonparametric curve estimation problems. To avoid these difficulties we use the technique, which is a kind of generalized reflection method involving reflecting a transformation of the data.
Název v anglickém jazyce
ROC curves as an aspect of classification
Popis výsledku anglicky
Receiver Operating Characteristic (ROC) analysis has its origin in signal detection theory, but most of the current work occurs in the medical decision making community. Now, ROC curves have been widely used for evaluating the accuracy and discriminatingpower of a diagnostic test or statistical model. To derive a smooth estimate for the ROC curve, we use a kernel smoothing method. We estimate a distribution function by this process. It is well known now that kernel distribution estimators are not consistent when estimating a distribution near the finite end points of its support. This is due to boundary effects that occur in nonparametric curve estimation problems. To avoid these difficulties we use the technique, which is a kind of generalized reflection method involving reflecting a transformation of the data.
Klasifikace
Druh
O - Ostatní výsledky
CEP obor
BA - Obecná matematika
OECD FORD obor
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Návaznosti výsledku
Projekt
<a href="/cs/project/LC06024" target="_blank" >LC06024: Centrum Jaroslava Hájka pro teoretickou a aplikovanou statistiku</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2009
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů