An improved multiclass LogitBoost using adaptive-one-vs-one

Abstract

LogitBoost is a popular Boosting variant that can be applied to either binary or multi-class classification. From a statistical viewpoint LogitBoost can be seen as additive tree regression by minimizing the Logistic loss. Following this setting, it is still non-trivial to devise a sound multi-class LogitBoost compared with to devise its binary counterpart… (More)
DOI: 10.1007/s10994-014-5434-3

Topics

23 Figures and Tables