Binary text classification using genetic programming with crossover-based oversampling for imbalanced datasets.
Mona Khalifa A. AljeroNazife DimililerPublished in: Turkish J. Electr. Eng. Comput. Sci. (2023)
Keyphrases
- imbalanced datasets
- text classification
- class imbalance
- minority class
- feature selection
- class distribution
- sampling methods
- cost sensitive learning
- learning from imbalanced data
- cost sensitive
- text categorization
- naive bayes
- genetic algorithm
- text mining
- active learning
- decision trees
- genetic programming
- imbalanced data
- feature selection algorithms
- machine learning
- binary classification
- unlabeled data
- high dimensionality
- evolutionary algorithm
- ensemble methods
- training dataset
- knn
- data cleaning
- concept drift
- genetic algorithm ga
- binary classifiers
- fitness function
- multi label
- high dimensional
- supervised learning
- probability estimation
- original data
- training set
- feature extraction
- data mining