Ensemble of extreme learning machines for diagnosing bearing defects in non-stationary environments under class imbalance condition.
Roozbeh Razavi-FarMehrdad SaifPublished in: SSCI (2016)
Keyphrases
- class imbalance
- extreme learning machines
- random subspaces
- imbalanced data
- binary classification problems
- class distribution
- active learning
- cost sensitive
- feature selection
- concept drift
- cost sensitive learning
- high dimensionality
- sampling methods
- training set
- base classifiers
- majority class
- ensemble methods
- ensemble learning
- imbalanced datasets
- small disjuncts
- neural network
- ensemble classifier
- random forest
- training data
- minority class
- machine learning
- data sets
- nearest neighbor
- learning algorithm
- prediction accuracy
- non stationary
- prior knowledge