A comparison of the bagging and the boosting methods using the decision trees classifiers.
Kristína MachovaMiroslav PusztaFrantisek BarcákPeter BednárPublished in: Comput. Sci. Inf. Syst. (2006)
Keyphrases
- decision trees
- ensemble learning
- ensemble methods
- majority voting
- weak classifiers
- ensemble classification
- classification trees
- machine learning algorithms
- machine learning methods
- ensemble classifier
- decision tree algorithm
- multiple classifier systems
- weak learners
- feature selection
- naive bayes
- benchmark datasets
- classifier ensemble
- meta learning
- random forest
- classification models
- training data
- prediction accuracy
- base learners
- training set
- multiclass classification
- decision stumps
- cost sensitive