Results 1 - 10 of 3,099

The Relationship Between Precision-Recall and ROC Curves

by Jesse Davis, Mark Goadrich - In ICML ’06: Proceedings of the 23rd international conference on Machine learning , 2006
"... Receiver Operator Characteristic (ROC) curves are commonly used to present results for binary decision problems in machine learning. However, when dealing with highly skewed datasets, Precision-Recall (PR) curves give a more informative picture of an algorithm’s performance. We show that a deep conn ..."
Abstract - Cited by 415 (4 self) - Add to MetaCart
Receiver Operator Characteristic (ROC) curves are commonly used to present results for binary decision problems in machine learning. However, when dealing with highly skewed datasets, Precision-Recall (PR) curves give a more informative picture of an algorithm’s performance. We show that a deep

ROC curves and the

by Andrew P. Bradley
"... 2 test ..."
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The use of the area under the ROC curve in the evaluation of machine learning algorithms

by Andrew P. Bradley - PATTERN RECOGNITION , 1997
"... In this paper we investigate the use of the area under the receiver operating characteristic (ROC) curve (AUC) as a performance measure for machine learning algorithms. As a case study we evaluate six machine learning algorithms (C4.5, Multiscale Classifier, Perceptron, Multi-layer Perceptron, k-Ne ..."
Abstract - Cited by 685 (3 self) - Add to MetaCart
In this paper we investigate the use of the area under the receiver operating characteristic (ROC) curve (AUC) as a performance measure for machine learning algorithms. As a case study we evaluate six machine learning algorithms (C4.5, Multiscale Classifier, Perceptron, Multi-layer Perceptron, k

Repairing concavities in ROC curves

by Peter Flach - In: Proc. 2003 UK Workshop on Computational Intelligence , 2003
"... In this paper we propose methods to detect and repair concavities in ROC curves by manipulating model predictions. We introduce two model assembly algorithms. Algorithm SwapOne aims to improve the Area Under the ROC Curve (AUC) of a probabilistic classifier by investigating three models from differe ..."
Abstract - Cited by 27 (6 self) - Add to MetaCart
In this paper we propose methods to detect and repair concavities in ROC curves by manipulating model predictions. We introduce two model assembly algorithms. Algorithm SwapOne aims to improve the Area Under the ROC Curve (AUC) of a probabilistic classifier by investigating three models from

when estimating ROC curves

by Peter G Hall, Rob J Hyndman, Width Selection, Peter G. Hall, Rob J. Hyndman , 2002
"... Abstract: The receiver operating characteristic (ROC) curve is used to describe the performance of a diagnostic test which classifies observations into two groups. We introduce a new method for selecting bandwidths when computing kernel estimates of ROC curves. Our technique allows for interaction b ..."
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Abstract: The receiver operating characteristic (ROC) curve is used to describe the performance of a diagnostic test which classifies observations into two groups. We introduce a new method for selecting bandwidths when computing kernel estimates of ROC curves. Our technique allows for interaction

On bootstrapping the ROC curve

by Patrice Bertail, Stéphan Clémençon, Nicolas Vayatis - In Proc. of Neur , 2008
"... This paper is devoted to thoroughly investigating how to bootstrap the ROC curve, a widely used visual tool for evaluating the accuracy of test/scoring statistics in the bipartite setup. The issue of confidence bands for the ROC curve is considered and a resampling procedure based on a smooth versio ..."
Abstract - Cited by 1 (1 self) - Add to MetaCart
This paper is devoted to thoroughly investigating how to bootstrap the ROC curve, a widely used visual tool for evaluating the accuracy of test/scoring statistics in the bipartite setup. The issue of confidence bands for the ROC curve is considered and a resampling procedure based on a smooth

Resampling ROC curves

by Ndèye Niang, Gilbert Saporta, Rue Saint Martin
"... Resampling procedures allows a better use of ROC curves and AUC for predictive purposes. We also address a drawback of AUC for the comparison of ROC curves which are crossing, by recommending the use of partial AUC. 1 ROC curve and AUC as a measure of performance Receiver operating characteristic (R ..."
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Resampling procedures allows a better use of ROC curves and AUC for predictive purposes. We also address a drawback of AUC for the comparison of ROC curves which are crossing, by recommending the use of partial AUC. 1 ROC curve and AUC as a measure of performance Receiver operating characteristic

Confidence bands for roc curves

by Sofus A. Macskassy, Foster Provost - In CeDER Working Paper , 2003
"... In this paper we study techniques for generating and evaluat-ing confidence bands on ROC curves. ROC curve evaluation is rapidly becoming a commonly used evaluation metric in machine learning, although evaluating ROC curves has thus far been lim-ited to studying the area under the curve (AUC) or gen ..."
Abstract - Cited by 7 (0 self) - Add to MetaCart
In this paper we study techniques for generating and evaluat-ing confidence bands on ROC curves. ROC curve evaluation is rapidly becoming a commonly used evaluation metric in machine learning, although evaluating ROC curves has thus far been lim-ited to studying the area under the curve (AUC

ROC Curves in medical decision

by Ana Cristina Braga, Lino Costa, Pedro Oliveira
"... Abstract The accurate medical diagnostic of a disease condition is fundamental for a correct medical decision. Disease screening programs are based, in general, in diagnostic tests which provide a binary response: a subject is classified as positive, if the test result is above a given threshold, an ..."
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, and negative, otherwise. Therefore, false positive and false negative classifications can be generated. The performance of test can be evaluated by ROC curves which defined, for a given threshold, the compro-mise between Sensitivity and Specificity, i.e., the True and False Positive fractions. In this work, we

ROC CURVE ESTIMATION: AN OVERVIEW

by Luzia Gonçalves, Ana Subtil, M. Rosário Oliveira, Patricia De Zea Bermudez
"... • This work overviews some developments on the estimation of the Receiver Operating Characteristic (ROC) curve. Estimation methods in this area are constantly being developed, adjusted and extended, and it is thus impossible to cover all topics and areas of application in a single paper. Here, we fo ..."
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• This work overviews some developments on the estimation of the Receiver Operating Characteristic (ROC) curve. Estimation methods in this area are constantly being developed, adjusted and extended, and it is thus impossible to cover all topics and areas of application in a single paper. Here, we
Results 1 - 10 of 3,099