Probability Estimates for Multi-Class Classification by Pairwise Coupling 论文
2003Journal of Machine Learning Research引用 980
Anomaly Detection Techniques and ApplicationsFace and Expression RecognitionAdvanced Statistical Methods and Models
摘要
Pairwise coupling is a popular multi-class classification method that combines all comparisons for each pair of classes. This paper presents two approaches for obtaining class probabilities. Both methods can be reduced to linear systems and are easy to implement. We show conceptually and experimentally that the proposed approaches are more stable than the two existing popular methods: voting and the method by Hastie and Tibshirani (1998).