Bagging of credal decision trees for imprecise classification.
Serafín Moral-GarcíaCarlos Javier MantasJavier G. CastellanoMaría D. BenítezJoaquín AbellánPublished in: Expert Syst. Appl. (2020)
Keyphrases
- decision trees
- ensemble methods
- predictive accuracy
- decision rules
- machine learning
- training set
- naive bayes
- random forests
- logistic regression
- random forest
- decision tree classifiers
- machine learning algorithms
- classification models
- classification rules
- majority voting
- base classifiers
- decision tree learning algorithm
- classification accuracy
- training data
- decision tree induction
- rule sets
- decision tree algorithm
- attribute selection
- decision tree learners
- support vector
- decision tree learning
- concept drifting data streams
- fuzzy decision trees
- classifier ensemble
- classification trees
- regression trees
- class imbalance
- class distribution
- machine learning methods
- classification algorithm
- support vector machine
- feature selection