Margin-based Ranking and an Equivalence between AdaBoost and RankBoost
We study boosting algorithms for learning to rank. We give a general margin-based bound for ranking based on covering numbers for the hypothesis space. Our bound suggests that algorithms that maximize the ranking margin will generalize well. We then describe a new algorithm, smooth margin ranking, t...
| Main Authors: | , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
MIT Press,
2010-03-05T16:33:37Z.
|
| Subjects: | |
| Online Access: | Get fulltext |