ROC curves as an aspect of classification

Result code in 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>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
ROC curves as an aspect of classification
Original language description
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.
Czech name
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Czech description
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Project
<a href="/en/project/LC06024" target="_blank" >LC06024: Jaroslav Hájek Center for Theoretical and Applied Statistics</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2009
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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