Exploring the Impact of Purity Gap Gain on the Efficiency and Effectiveness of Random Forest Feature Selection.
Mandlenkosi Victor GwetuJules-Raymond TapamoSerestina ViririPublished in: ICCCI (1) (2019)
Keyphrases
- knn
- random forest
- feature selection
- feature set
- text categorization
- decision trees
- random forests
- multi label
- selected features
- text classification
- feature reduction
- feature importance
- cancer classification
- rotation forest
- fold cross validation
- ensemble learning
- ensemble methods
- ensemble classifier
- machine learning
- neural network
- base classifiers
- feature ranking
- gene expression data
- logistic regression
- naive bayes
- active learning
- training data
- decision tree learning algorithms