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122
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KAIS
2010
14 years 11 months ago
2010
Real world data mining applications must address the issue of learning from imbalanced data sets. The problem occurs when the number of instances in one class greatly outnumbers t...
120
Voted
ICML
2005
IEEE
16 years 1 months ago
2005
IEEE
AdaBoost.OC has shown to be an effective method in boosting "weak" binary classifiers for multi-class learning. It employs the Error Correcting Output Code (ECOC) method...
115
Voted
FLAIRS
2008
15 years 3 months ago
2008
Building useful classification models can be a challenging endeavor, especially when training data is imbalanced. Class imbalance presents a problem when traditional classificatio...
87
Voted
BMCBI
2008
15 years 24 days ago
2008
Background: When predictive survival models are built from high-dimensional data, there are often additional covariates, such as clinical scores, that by all means have to be incl...
117
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ICML
2007
IEEE
16 years 1 months ago
2007
IEEE
A general framework is proposed for gradient boosting in supervised learning problems where the loss function is defined using a kernel over the output space. It extends boosting ...