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» Active Learning for Class Probability Estimation and Ranking
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AUSAI
2006
Springer
13 years 10 months ago
Lazy Learning for Improving Ranking of Decision Trees
Decision tree-based probability estimation has received great attention because accurate probability estimation can possibly improve classification accuracy and probability-based r...
Han Liang, Yuhong Yan
ICML
2008
IEEE
14 years 7 months ago
Cost-sensitive multi-class classification from probability estimates
For two-class classification, it is common to classify by setting a threshold on class probability estimates, where the threshold is determined by ROC curve analysis. An analog fo...
Deirdre B. O'Brien, Maya R. Gupta, Robert M. Gray
MCS
2005
Springer
13 years 12 months ago
A Probability Model for Combining Ranks
Mixed Group Ranks is a parametric method for combining rank based classiers that is eective for many-class problems. Its parametric structure combines qualities of voting methods...
Ofer Melnik, Yehuda Vardi, Cun-Hui Zhang
TIP
2008
185views more  TIP 2008»
13 years 5 months ago
Active Learning Methods for Interactive Image Retrieval
Active learning methods have been considered with increased interest in the statistical learning community. Initially developed within a classification framework, a lot of extensio...
Philippe Henri Gosselin, Matthieu Cord
ICTAI
2006
IEEE
14 years 12 days ago
Improve Decision Trees for Probability-Based Ranking by Lazy Learners
Existing work shows that classic decision trees have inherent deficiencies in obtaining a good probability-based ranking (e.g. AUC). This paper aims to improve the ranking perfor...
Han Liang, Yuhong Yan