Bagging and Boosting a Treebank Parser
| dc.creator | Henderson, John C. | |
| dc.creator | Brill, Eric | |
| dc.date | 2000-06-05 | |
| dc.date.accessioned | 2026-07-25T23:55:53Z | |
| dc.description | Bagging and boosting, two effective machine learning techniques, are applied to natural language parsing. Experiments using these techniques with a trainable statistical parser are described. The best resulting system provides roughly as large of a gain in F-measure as doubling the corpus size. Error analysis of the result of the boosting technique reveals some inconsistent annotations in the Penn Treebank, suggesting a semi-automatic method for finding inconsistent treebank annotations. | |
| dc.description | 8 pages | |
| dc.identifier | https://arxiv.org/abs/cs/0006011 | |
| dc.identifier | http://arxiv.org/abs/cs/0006011 | |
| dc.identifier | Proceedings of the 1st Meeting of the North American Chapter of the Association for Computational Linguistics (NAACL-2000), pages 34-41 | |
| dc.identifier.uri | https://dspace.dare.co.zw/handle/123456789/102598 | |
| dc.subject | Computation and Language | |
| dc.subject | I.2.7 | |
| dc.title | Bagging and Boosting a Treebank Parser | |
| dc.type | text |