Enhancing the effectiveness and interpretability of decision tree and rule induction classifiers with evolutionary training set selection over imbalanced problems.
Salvador GarcíaAlberto FernándezFrancisco HerreraPublished in: Appl. Soft Comput. (2009)
Keyphrases
- decision trees
- rule induction
- training set
- binary classification problems
- training data
- decision rules
- test set
- naive bayes
- machine learning algorithms
- instance based learning
- rule induction algorithm
- genetic algorithm
- classification rules
- data sets
- rough set theory
- supervised learning
- classification accuracy
- active learning
- feature selection
- machine learning
- training examples
- rough sets
- class labels
- nearest neighbor
- rule sets
- classification error
- decision tree algorithm
- minority class
- rule induction methods
- class distribution
- classification algorithm
- training samples
- feature space
- neural network