Pruning in Ordered Regression Bagging Ensembles.
Daniel Hernández-LobatoGonzalo Martínez-MuñozAlberto SuárezPublished in: IJCNN (2006)
Keyphrases
- ensemble methods
- base learners
- ensemble learning
- ensemble selection
- random forests
- tree ensembles
- imbalanced data
- neural network ensembles
- base classifiers
- ensemble members
- decision trees
- regression problems
- regression trees
- linear regression
- learning machines
- gradient boosting
- rotation forest
- regression model
- classifier ensemble
- tree induction
- prediction accuracy
- decision tree ensembles
- model averaging
- learning scheme
- pruning method
- search space
- random forest
- benchmark datasets
- randomized trees
- generalization ability
- meta learning
- cost sensitive
- ensemble classifier
- model selection
- ridge regression
- variable selection
- ensemble classification
- cross validation
- conformal prediction
- weighted voting
- negative correlation learning
- majority voting
- machine learning methods
- classification algorithm
- loss function
- regression algorithm
- selection strategy
- generalization error
- logistic regression
- genetic programming
- support vector
- decision tree induction
- concept drift
- test data
- least squares
- training set