Integration of Bagging and Boosting with a New Reweighting Technique.
Yoshiaki YasumuraNaho KitaniKuniaki UeharaPublished in: CIMCA/IAWTIC (2005)
Keyphrases
- ensemble learning
- base classifiers
- ensemble methods
- random forest
- randomized trees
- generalization ability
- gradient boosting
- weak learners
- multi class
- ensemble classification
- base learners
- decision trees
- classification error
- random forests
- benchmark datasets
- prediction accuracy
- training set
- ensemble classifier
- meta learning
- learning machines
- classifier ensemble
- imbalanced data
- decision stumps
- learning algorithm
- majority voting
- decision tree ensembles
- class distribution
- naive bayes
- training samples
- feature set
- boosting algorithms
- weak classifiers
- adaboost algorithm
- test data
- data fusion
- individual classifiers
- class labels
- tree induction
- support vector