Boosting in the Limit: Maximizing the Margin of Learned Ensembles.
Adam J. GroveDale SchuurmansPublished in: AAAI/IAAI (1998)
Keyphrases
- ensemble methods
- ensemble learning
- base classifiers
- boosting algorithms
- training set
- decision stumps
- base learners
- decision trees
- weighted voting
- ensemble classifier
- decision tree ensembles
- soft margin
- multiple classifier systems
- random forests
- loss function
- decision boundary
- class labels
- machine learning
- cost sensitive
- weak classifiers
- supervised learning
- weak learners
- multi class
- classification accuracy
- support vector
- learning algorithm