Solving class imbalance problem using bagging, boosting techniques, with and without using noise filtering method.
Gillala RekhaAmit Kumar TyagiV. Krishna ReddyPublished in: Int. J. Hybrid Intell. Syst. (2019)
Keyphrases
- filtering method
- class imbalance
- class distribution
- imbalanced data
- base classifiers
- cost sensitive
- ensemble methods
- ensemble learning
- post processing
- active learning
- feature selection
- class noise
- multi class
- base learners
- concept drift
- machine learning
- high dimensionality
- learning algorithm
- sampling methods
- decision trees
- training set
- denoising
- random forest
- minority class
- ensemble classifier
- classification error
- naive bayes
- weak classifiers
- random forests
- filtering algorithm
- class labels
- boosting algorithms
- training data
- fingerprint images
- meta learning
- prediction accuracy
- data streams
- generalization ability
- feature extraction
- machine learning methods