106 search results - page 7 / 22 » Boosting the Area under the ROC Curve |
DICTA
2007
14 years 11 months ago
2007
Texture analysis of the liver for the diagnosis of cirrhosis is usually region-of-interest (ROI) based. Integrity of the label of ROI data may be a problem due to sampling. This p...
ICONIP
2008
14 years 11 months ago
2008
In this paper, we present the performance of machine learning-based methods for detection of phishing sites. We employ 9 machine learning techniques including AdaBoost, Bagging, S...
DATAMINE
2008
14 years 9 months ago
2008
Rules are commonly used for classification because they are modular, intelligible and easy to learn. Existing work in classification rule learning assumes the goal is to produce ca...
76
Voted
ICML
2003
IEEE
15 years 10 months ago
2003
IEEE
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,...
IJPRAI
2010
14 years 8 months ago
2010
: AUC-SVM directly maximizes the area under the ROC curve (AUC) through minimizing its hinge loss relaxation, and the decision function is determined by those support vector sample...