ABC-boost: adaptive base class boost for multi-class classification

We propose abc-boost (adaptive base class boost) for multi-class classification and present abc-mart, an implementation of abcboost, based on the multinomial logit model. The key idea is that, at each boosting iteration, we adaptively and greedily choose a base class. Our experiments on public datasets demonstrate the improvement of abc-mart over the original mart algorithm.

• Type: Conference
• Year: 2009
• Where: ICML
• Authors: Ping Li
• Keywords: Base Class Boost, ICML 2009, Machine Learning, Multinomial Logit Model, Original Mart Algorithm