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» Confidence Intervals for the Area Under the ROC Curve
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ICML
2003
IEEE
14 years 8 months ago
Optimizing Classifier Performance via an Approximation to the Wilcoxon-Mann-Whitney Statistic
When the goal is to achieve the best correct classification rate, cross entropy and mean squared error are typical cost functions used to optimize classifier performance. However,...
Lian Yan, Robert H. Dodier, Michael Mozer, Richard...
IS
2010
13 years 6 months ago
ROC analysis of a fatigue classifier for vehicular drivers
— Few systems have been developed for the detection of fatigue / stress level of a vehicular driver in order to monitor and control the alertness level for preventing road accide...
Mahesh M. Bundele, Rahul Banerjee
BMCBI
2007
141views more  BMCBI 2007»
13 years 7 months ago
Artificial neural network models for prediction of intestinal permeability of oligopeptides
Background: Oral delivery is a highly desirable property for candidate drugs under development. Computational modeling could provide a quick and inexpensive way to assess the inte...
Eunkyoung Jung, Junhyoung Kim, Minkyoung Kim, Dong...
FLAIRS
2008
13 years 9 months ago
Using Genetic Programming to Increase Rule Quality
Rule extraction is a technique aimed at transforming highly accurate opaque models like neural networks into comprehensible models without losing accuracy. G-REX is a rule extract...
Rikard König, Ulf Johansson, Lars Niklasson
ECML
2007
Springer
14 years 1 months ago
An Improved Model Selection Heuristic for AUC
Abstract. The area under the ROC curve (AUC) has been widely used to measure ranking performance for binary classification tasks. AUC only employs the classifier’s scores to ra...
Shaomin Wu, Peter A. Flach, Cèsar Ferri Ram...