Optimizing classifiers for imbalanced training sets

Support Vector Machines for Classification in Nonstandard Situations

Machine Learning

Tuning Cost-Sensitive Boosting and Its Application to Melanoma Diagnosis

MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems

KBA: Kernel Boundary Alignment Considering Imbalanced Data Distribution

IEEE Transactions on Knowledge and Data Engineering

Risk-sensitive loss functions for sparse multi-category classification problems

Information Sciences: an International Journal

Imbalanced SVM Learning with Margin Compensation

ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks

Learning from imbalanced data in surveillance of nosocomial infection

Artificial Intelligence in Medicine

Margin calibration in SVM class-imbalanced learning

Neurocomputing

Exploratory undersampling for class-imbalance learning

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Kernel-matching pursuits with arbitrary loss functions

IEEE Transactions on Neural Networks

VQSVM: A case study for incorporating prior domain knowledge into inductive machine learning

Neurocomputing

Identification of intestinal motility events of capsule endoscopy video analysis

ACIVS'05 Proceedings of the 7th international conference on Advanced Concepts for Intelligent Vision Systems

Shedding light on the asymmetric learning capability of AdaBoost

Pattern Recognition Letters

Double-base asymmetric AdaBoost

Neurocomputing