An Adaptive Version of the Boost by Majority Algorithm
Machine Learning
A decision-theoretic generalization of on-line learning and an application to boosting
EuroCOLT '95 Proceedings of the Second European Conference on Computational Learning Theory
Reducing multiclass to binary: a unifying approach for margin classifiers
The Journal of Machine Learning Research
Approximating the multiclass ROC by pairwise analysis
Pattern Recognition Letters
Mining whole-sample mass spectrometry proteomics data for biomarkers - An overview
Expert Systems with Applications: An International Journal
The ROC skeleton for multiclass ROC estimation
Pattern Recognition Letters
Hi-index | 0.10 |
A simple solution is proposed to the problem of conveying a classifier's performance to a universal standard when misclassification costs are not equal. An application of this metric in the field of boosting is briefly described.