Classification Performance of Bagging and Boosting Type Ensemble Methods with Small Training Sets.
Faisal ZamanHideo HirosePublished in: New Gener. Comput. (2011)
Keyphrases
- ensemble methods
- decision trees
- majority voting
- machine learning methods
- benchmark datasets
- generalization ability
- ensemble classification
- base learners
- ensemble learning
- prediction accuracy
- ensemble classifier
- base classifiers
- classifier ensemble
- random forests
- random forest
- imbalanced data
- random subspace
- rotation forest
- randomized trees
- individual classifiers
- binary classification
- ensemble feature selection
- decision tree ensembles
- machine learning
- classification accuracy
- classifier fusion
- multiple classifier systems
- weak learners
- feature subset
- ensemble members
- bootstrap sampling
- classification algorithm
- support vector
- subspace methods
- boosting algorithms
- cross validation
- training set
- training data
- multi class
- supervised learning
- training samples
- naive bayes