Empirical and Kernel Estimation of the ROC Curve

Aleksandra Katarzyna Baszczyńska

doi:10.18778/0208-6018.311.06

Authors

Aleksandra Katarzyna Baszczyńska University of Łódź

DOI:

https://doi.org/10.18778/0208-6018.311.06

Keywords:

ROC curve, empirical estimator, kernel method, smoothing parameter, kernel function

Abstract

The paper presents chosen methods for estimating the ROC (Receiver Operating Characteristic) curve, including parametric and nonparametric procedures. Nonparametric approach may involve the use of empirical method or kernel method of the ROC curve estimation. In the analysis, an attempt of comparison of empirical and kernel ROC estimators is done, considering the impact of sample size, choice of smoothing parameter and kernel function in kernel estimation on the results of the estimation. Based on the results of simulation studies, some suggestions, useful in the procedures of nonparametric ROC curve are determined.

Downloads

Download data is not yet available.

Author Biography

Aleksandra Katarzyna Baszczyńska, University of Łódź

The analysis of properties of kernel methods.

References

Chrzanowski M. (2014), Weighted Empirical Likelihood Inference for the Area under the ROC Curve, Journal of Statistical Planning and Inference, 147, 159-172.

Domański C., Pekasiewicz D., Baszczyńska A., Witaszczyk A. (2014), Testy statystyczne w procesie podejmowania decyzji, Wydawnictwo Uniwersytetu Łódzkiego, Łódź.

Fawcett T. (2006), An Introduction to ROC Analysis, Pattern Recognition Letters, 27, 861-874.

Harańczyk G. (2010), Krzywe ROC, czyli ocena jakości klasyfikatora i poszukiwanie optymalnego punktu odcięcia, Statsoft Polska, www.statsoft.pl/czytelnia.html.

Horová I., Koláček J., Zelinka J. (2012), Kernel Smoothing in Matlab. Theory and Practice of Kernel Smoothing, World Scientific, New Jersey.

Krzanowski W., Hand D. (2009), ROC Curves for Continuous Data, CRC Press.

Krzyśko M., Wołyński W., Górecki T., Skorzybut M. (2008), Systemy uczące się. Rozpoznawanie wzorców, analiza skupień i redukcja wymiarowości, Wydawnictwa Naukowo-Techniczne, Warszawa.

Lloyd C. (2002), Estimation of a Convex ROC Curves, Statistics and Probability Letters, 59, 1, 99-111.

Marron J., Wand M. (1992), Exact Mean Integrated Squared Error, The Annals of Statistics, 20, 2, 712-736.

Misztal M. (2014), On the Selected Methods for Evaluating Classification Models, Acta Universitatis Lodziensis Folia Oeconomica , 3 (302), 161-173.

Ruzgas T., Drulyrè I. (2013), Kernel Density Estimation for Gaussian Mixture Models, Lithuanian Journal of Statistics, 52, 1, 14-21.