Conference submission (2/1/02). Incorporating Prior Knowledge into Boosting
by Robert E. Schapire, Marie Rochery, Mazin Rahim, Narendra Gupta
http://www.research.att.com/~schapire/cgi-bin/uncompress-papers/boostknowledge.ps
Add To MetaCart
Abstract:
We describe a modification to the AdaBoost algorithm that permits the incorporation of prior human knowledge as a means of compensating for a shortage of training data. We give a convergence result for the algorithm. We describe experiments on four datasets showing that prior knowledge can substantially improve performance. 1.
Citations
| 1133 | A decision-theoretic generalization of online learning and an application to boosting – Freund, Schapire - 1995 |
| 575 | Combining labeled and unlabeled data with co-training – Blum, Mitchell - 1998 |
| 282 | NewsWeeder: learning to filter netnews – Lang - 1995 |
| 245 | Boostexter: A boostingbased system for text categorization – Schapire, Singer - 2000 |
| 239 | Unsupervised models for named entity classification – Collins, Singer - 1999 |
| 151 | Heterogeneous Uncertainty Sampling for Supervised Learning – Lewis, Catlett - 1994 |
| 118 | Logistic regression, adaboost and bregman distances – Collins, Schapire, et al. - 2002 |
| 57 | How may I help you – Gorin, Riccardi, et al. - 1997 |
| 51 | Schapire and Yoram Singer. Improved boosting algorithms using confidence-rated predictions – Robert - 1999 |
| 39 | Training Text Classifiers by Uncertainty Sampling – Lewis, Gale - 1994 |
| 6 | Combining prior knowledge and boosting for call classification in spoken language dialogue – Rochery, Schapire, et al. - 2002 |
