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» Optimizing abstaining classifiers using ROC analysis
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CVIU
2007
240views more  CVIU 2007»
13 years 7 months ago
Objective evaluation of approaches of skin detection using ROC analysis
Skin detection is an important indicator of human presence and actions in many domains, including interaction, interfaces and security. It is commonly performed in three steps: tr...
Stephen Schmugge, Sriram Jayaram, Min C. Shin, Leo...
JUCS
2008
155views more  JUCS 2008»
13 years 7 months ago
Combining Classifiers in the ROC-space for Off-line Signature Verification
: In this work we present a strategy for off-line signature verification. It takes into account a writer-independent model which reduces the pattern recognition problem to a 2-clas...
Luiz S. Oliveira, Edson J. R. Justino, Robert Sabo...
IDEAL
2005
Springer
14 years 27 days ago
Evolving Neural Networks for the Classification of Malignancy Associated Changes
Malignancy Associated Changes are subtle changes to the nuclear texture of visually normal cells in the vicinity of a cancerous or precancerous lesion. We describe a classifier for...
Jennifer Hallinan
SDM
2007
SIAM
104views Data Mining» more  SDM 2007»
13 years 8 months ago
Boosting Optimal Logical Patterns Using Noisy Data
We consider the supervised learning of a binary classifier from noisy observations. We use smooth boosting to linearly combine abstaining hypotheses, each of which maps a subcube...
Noam Goldberg, Chung-chieh Shan
NIPS
2004
13 years 8 months ago
Confidence Intervals for the Area Under the ROC Curve
In many applications, good ranking is a highly desirable performance for a classifier. The criterion commonly used to measure the ranking quality of a classification algorithm is ...
Corinna Cortes, Mehryar Mohri