Software defect prediction using a cost sensitive decision forest and voting, and a potential solution to the class imbalance problem.
Michael J. SiersMd Zahidul IslamPublished in: Inf. Syst. (2015)
Keyphrases
- class imbalance
- cost sensitive
- software defect prediction
- cost sensitive learning
- class distribution
- misclassification costs
- multi class
- active learning
- naive bayes
- sampling methods
- minority class
- imbalanced data
- feature selection
- machine learning
- boosting algorithms
- data sets
- base classifiers
- principal component analysis
- decision trees