Effect of Feature Selection, SMOTE and under Sampling on Class Imbalance Classification.
Nadeem QaziKamran RazaPublished in: UKSim (2012)
Keyphrases
- class imbalance
- feature selection
- class distribution
- cost sensitive
- active learning
- high dimensionality
- cost sensitive learning
- imbalanced datasets
- imbalanced data
- minority class
- imbalanced data sets
- majority class
- class imbalanced
- concept drift
- sampling methods
- classification accuracy
- highly skewed
- text classification
- text categorization
- feature set
- test set
- imbalanced class distribution
- classification models
- pairwise
- pattern recognition
- support vector
- learning algorithm
- feature extraction
- training data
- feature space
- model selection
- training samples
- classification algorithm
- high dimensional data