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» Learning with the Set Covering Machine
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ECML
2007
Springer
14 years 3 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...
ECML
2007
Springer
14 years 3 months ago
Nondeterministic Discretization of Weights Improves Accuracy of Neural Networks
Abstract. The paper investigates modification of backpropagation algorithm, consisting of discretization of neural network weights after each training cycle. This modification, a...
Marcin Wojnarski
ECML
2007
Springer
14 years 3 months ago
Avoiding Boosting Overfitting by Removing Confusing Samples
Boosting methods are known to exhibit noticeable overfitting on some datasets, while being immune to overfitting on other ones. In this paper we show that standard boosting algorit...
Alexander Vezhnevets, Olga Barinova
ECML
2007
Springer
14 years 3 months ago
Clustering Trees with Instance Level Constraints
Abstract. Constrained clustering investigates how to incorporate domain knowledge in the clustering process. The domain knowledge takes the form of constraints that must hold on th...
Jan Struyf, Saso Dzeroski
MLDM
2007
Springer
14 years 3 months ago
Ensemble-based Feature Selection Criteria
Recursive Feature Elimination (RFE) combined with feature ranking is an effective technique for eliminating irrelevant features when the feature dimension is large, but it is diffi...
Terry Windeatt, Matthew Prior, Niv Effron, Nathan ...