Comparing Boosting and Bagging for Decision Trees of Rankings.
Antonella PlaiaSimona BuscemiJohannes FürnkranzEneldo Loza MencíaPublished in: J. Classif. (2022)
Keyphrases
- decision trees
- ensemble methods
- base classifiers
- decision tree ensembles
- ensemble learning
- random forests
- random forest
- decision tree algorithm
- tree induction
- boosted decision trees
- base learners
- decision tree induction
- naive bayes
- meta learning
- decision stumps
- ensemble classifier
- ensemble classification
- multi class
- machine learning algorithms
- decision tree learning
- classification trees
- decision tree learning algorithms
- machine learning
- classifier ensemble
- benchmark datasets
- class distribution
- randomized trees
- training set
- prediction accuracy
- generalization ability
- learning algorithm
- training data
- probability estimates
- logistic regression
- classification rules
- gradient boosting
- regression trees
- classification models
- machine learning methods
- majority voting
- individual classifiers
- pairwise comparisons
- induction algorithms
- support vector machine
- cost sensitive
- decision tree induction algorithm
- weak classifiers