The accuracy of Random Forest performance can be improved by conducting a feature selection with a balancing strategy.
Maria Irmina PrasetiyowatiNur Ulfa MaulideviKridanto SurendroPublished in: PeerJ Comput. Sci. (2022)
Keyphrases
- random forest
- fold cross validation
- feature set
- feature reduction
- feature selection
- selected features
- random forests
- classification accuracy
- decision trees
- ensemble methods
- decision tree learning algorithms
- prediction accuracy
- feature ranking
- cancer classification
- feature importance
- rotation forest
- multi class
- ensemble learning
- ensemble classifier
- active learning
- feature extraction
- support vector
- base classifiers
- multi label
- text categorization
- feature space
- text classification
- classification models
- learning algorithm