Investigating New Bootstrapping Approaches of Bagging Classifiers to Account for Class Imbalance in Bioinformatics Datasets.
Alireza FazelpourTaghi M. KhoshgoftaarDavid J. DittmanAmri NapolitanoPublished in: ICMLA (2015)
Keyphrases
- imbalanced data
- class imbalance
- binary classification problems
- sampling methods
- imbalanced datasets
- class distribution
- majority class
- minority class
- imbalanced data sets
- ensemble methods
- decision trees
- active learning
- ensemble classifier
- ensemble learning
- class imbalanced
- machine learning methods
- training set
- data mining
- majority voting
- support vector
- cost sensitive learning
- classification algorithm
- multi class
- feature selection algorithms
- machine learning
- machine learning algorithms
- classifier ensemble
- cost sensitive
- linear classifiers
- benchmark datasets
- feature selection
- training data
- bayesian networks
- support vector machine
- learning process
- meta learning
- feature set
- concept drift
- svm classifier