An insight into the effects of class imbalance and sampling on classification accuracy in credit risk assessment.
Kristina AndricDamir KalpicZoran BohacekPublished in: Comput. Sci. Inf. Syst. (2019)
Keyphrases
- class imbalance
- sampling methods
- classification accuracy
- majority class
- minority class
- imbalanced data
- class distribution
- feature selection
- imbalanced class distribution
- skewed data
- cost sensitive
- active learning
- class noise
- imbalanced datasets
- random sampling
- high dimensionality
- highly skewed
- feature space
- cost sensitive learning
- small disjuncts
- training set
- support vector
- data sets
- concept drift
- naive bayes
- training data
- bp neural network
- neural network
- sampling algorithm
- multi class
- high dimensional
- face recognition
- decision trees