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Receiver operating characteristic
Known as:
Receiver operator curve
, C-statistic
, Receiver operator characteristic
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In statistics, a receiver operating characteristic (ROC), or ROC curve, is a graphical plot that illustrates the performance of a binary classifier…
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Related topics
Related topics
35 relations
Accuracy paradox
Algorithm
Base rate
Binary classification
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Broader (4)
Biostatistics
Data mining
Detection theory
Statistical classification
Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2009
Highly Cited
2009
Receiver Operating Characteristic
P. Tan
Encyclopedia of Database Systems
2009
Corpus ID: 37809395
A polishing apparatus includes a turntable with an abrasive cloth mounted on an upper surface thereof, and a top ring disposed…
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Highly Cited
2008
Highly Cited
2008
Receiver Operating Characteristic Curve Confidence Intervals and Regions
J. Kerekes
IEEE Geoscience and Remote Sensing Letters
2008
Corpus ID: 15228729
Many researchers have presented results showing the empirical performance of target detection algorithms using hyperspectral or…
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Highly Cited
2007
Highly Cited
2007
Analyzing Receiver Operating Characteristic Curves with SAS
M. Gonen
2007
Corpus ID: 59624835
As a diagnostic decision-making tool, receiver operating characteristic (ROC) curves provide a comprehensive and visually…
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Highly Cited
2006
Highly Cited
2006
An introduction to ROC analysis
Tom Fawcett
Pattern Recognition Letters
2006
Corpus ID: 2027090
Highly Cited
2006
Highly Cited
2006
Maximum entropy modeling of species geographic distributions
Steven J. Phillips
,
Robert P. Anderson
,
R. Schapire
2006
Corpus ID: 10285111
Highly Cited
2006
Highly Cited
2006
The relationship between Precision-Recall and ROC curves
Jesse Davis
,
Mark H. Goadrich
International Conference on Machine Learning
2006
Corpus ID: 207159665
Receiver Operator Characteristic (ROC) curves are commonly used to present results for binary decision problems in machine…
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Highly Cited
2004
Highly Cited
2004
A study of the behavior of several methods for balancing machine learning training data
Gustavo E. A. P. A. Batista
,
R. Prati
,
M. C. Monard
SKDD
2004
Corpus ID: 207155015
There are several aspects that might influence the performance achieved by existing learning systems. It has been reported that…
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Review
2000
Review
2000
Predictive habitat distribution models in ecology
A. Guisan
,
N. Zimmermann
2000
Corpus ID: 17473639
Review
1997
Review
1997
A review of methods for the assessment of prediction errors in conservation presence/absence models
A. Fielding
,
J. Bell
Environmental Conservation
1997
Corpus ID: 54735661
Predicting the distribution of endangered species from habitat data is frequently perceived to be a useful technique. Models that…
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Highly Cited
1997
Highly Cited
1997
The use of the area under the ROC curve in the evaluation of machine learning algorithms
A. Bradley
Pattern Recognition
1997
Corpus ID: 13806304
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