| Creator |
|
| Language |
|
| Publisher |
|
|
|
| Date |
|
| Source Title |
|
| Vol |
|
| Publication Type |
|
| Access Rights |
|
| Related DOI |
|
|
|
| Related URI |
|
|
|
| Relation |
|
|
|
| Abstract |
Smooth boosting algorithms are variants of boosting methods which handle only smooth distributions on the data. They are proved to be noise-tolerant and can be used in the “boosting by filtering” sche...me, which is suitable for huge data. However, current smooth boosting algorithms have rooms for improvements: Among non-smooth boosting algorithms, real AdaBoost or InfoBoost, can perform more efficiently than typical boosting algorithms by using an information-based criterion for choosing hypotheses. In this paper, we propose a new smooth boosting algorithm with another information-based criterion based on Gini index. We show that it inherits the advantages of two approaches, smooth boosting and information-based approaches.show more
|
Export Mendeley
trcs225