adabag: An R Package for Classification with Boosting and Bagging
Boosting and bagging are two widely used ensemble methods for classification. Their common goal is to improve the accuracy of a classifier combining single classifiers which are slightly better than random guessing. Among the family of boosting algorithms, AdaBoost (adaptive boosting) is the best kn...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Foundation for Open Access Statistics
2013-09-01
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| Series: | Journal of Statistical Software |
| Online Access: | http://www.jstatsoft.org/index.php/jss/article/view/2082 |