Results 211 to 220 of about 304,364 (248)

Area under the ROC Curve of Enhanced Energy Detector

2013 11th International Conference on Frontiers of Information Technology, 2013
The area under the Receiver-Operating-Characteristic (ROC) curve of a detector is a simple and suitable figure-of-merit of its detection capability. However the problem of determining the Area-Under-the-Curve (AUC) of an ROC is a non-trivial exercise and hence it has gone usually unnoticed in literature.
Syed Safwan Khalid, Shafayat Abrar
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Feature Selection for Maximizing the Area Under the ROC Curve

2009 IEEE International Conference on Data Mining Workshops, 2009
Feature selection is an important pre-processing step for solving classification problems. A good feature selection method may not only improve the performance of the final classifier, but also reduce the computational complexity of it. Traditionally, feature selection methods were developed to maximize the classification accuracy of a classifier ...
Rui Wang 0022, Ke Tang 0001
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The Area under the ROC Curve and Its Competitors

Medical Decision Making, 1991
The area under the receiver operating characteristic (ROC) curve is a popular measure of the power of a (two-disease) diagnostic test, but it is shown here to be an inconsistent criterion: tests of indistinguishable clinical impacts may have different areas. A class of diagnosticity measures (DMs) of proven optimality is proposed instead. Once a regret(
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WTE Revisited – ROC Curves and Area Under the Curve

AAP Grand Rounds, 2015
original published in[OpenUrl][1][FREE Full Text][2] Imagine yourself listening to Morse code over a crackling radio – it is hard to distinguish signal from noise. You have to look for the perfect volume, because when you hear the signal better, you also hear more noise, and when you cut down on the noise, you also lose some of the signal.
Virginia Moyer, Daniel R. Neuspiel
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Maximizing the area under the ROC curve by pairwise feature combination

Pattern Recognition, 2008
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Claudio Marrocco, Robert P. W. Duin, Francesco Tortorella   +2 more
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The area under normal ROC curves

São Paulo Journal of Mathematical Sciences
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
João C. Prandini, Pedro A. Morettin, Chang Chiann   +2 more
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On Linear Combinations of Dichotomizers for Maximizing the Area Under the ROC Curve

IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2011
In this paper, we propose a method for the linear combination of several dichotomizers aimed at maximizing the area under the receiver operating characteristic (ROC) curve of the resulting classification system. This is particularly suited for real applications where it is difficult to exactly determine the key parameters such as costs and priors.
Claudio Marrocco, Mario Molinara, Francesco Tortorella   +2 more
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On estimating the area under the ROC curve in ranked set sampling

Statistical Methods in Medical Research, 2022
In medical research, the receiver operating characteristic curve is widely used to evaluate accuracy of a continuous biomarker. The area under this curve is known as an index for overall performance of the biomarker. This article develops three new estimators of the area under the receiver operating characteristic curve in ranked set sampling.
M. Mahdizadeh, Ehsan Zamanzade
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Bounds on the area under the ROC curve

Journal of the Optical Society of America A, 1999
Upper and lower bounds are derived for the area under the receiver-operating-characteristic (ROC) curve of binary hypothesis testing. These results are compared with the area-under-the-curve (AUC) approximation and the AUC lower bound recently reported by Barrett et al. [J. Opt. Soc. Am A15, 1520 (1998)].
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Equivalence of the statistics for replicability and area under the ROC curve

British Journal of Mathematical and Statistical Psychology, 2009
Two statistics, one recent and one well known, are shown to be equivalent. The recent statistic, p rep , gives the probability that the sign of an experimental effect is replicable by an experiment of equal power.
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