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ICML
2009
IEEE

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

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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.
Ping Li
Added 17 Nov 2009
Updated 17 Nov 2009
Type Conference
Year 2009
Where ICML
Authors Ping Li
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