Ji Zhu University of Michigan Ann Arbor, MI 48109 Saharon Rosset Data...  Home/Search
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Abstract: Boosting has been a very successful technique for solving the two-class classification problem. (Update)
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BibTeX entry: (Update)
@misc{ university-multiclass,
author = "Ji Zhu University",
title = "Multi-class AdaBoost",
url = "citeseer.ist.psu.edu/765990.html" }
Citations (may not include all citations):667 UCI repository of machine learning databases (context) - Merz, Murphy - 1998
657 Bagging predictors - Breiman - 1996
509 A decision theoretic generalization of on-line learning and .. - Freund, Schapire - 1997
236 Additive logistic regression: a statistical view of boosting - Friedman, Hastie et al. - 2000
214 Improved boosting algorithms using confidence-rated predicti.. - Schapire, Singer - 1999
140 The Elements of Statistical Learning (context) - Hastie, Tibshirani et al. - 2001
86 Reducing multiclass to binary: a unifying approach for margi.. - Allwein, Schapire et al. - 2000
70 Prediction games and arcing algorithms - Breiman - 1984
61 Greedy function approximation: a gradient boosting machine - Friedman - 2001
37 Another approach to polychotomous classification (context) - Friedman - 2004
27 Using output codes to boost multiclass learning problems - Schapire - 1997
22 Speaker Normalisation for Automatic Speech Recognition (context) - Deterding - 1989
8 A note on margin-based loss functions in classification - Lin - 2004
6 Multicategory support vector machines, theory, and applicati.. - Lee, Lin et al. - 2004
5 Boosting with the l 2 loss: regression and classification (context) - Buhlmann, Yu - 2003
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