Diversity-aware fairness testing of machine learning classifiers through hashing-based sampling.
Zhenjiang ZhaoTakahisa TodaTakashi KitamuraPublished in: Inf. Softw. Technol. (2024)
Keyphrases
- machine learning
- machine learning algorithms
- machine learning methods
- diversity measures
- decision trees
- machine learning approaches
- supervised classification
- feature selection
- bootstrap sampling
- classifier ensemble
- pattern recognition
- test set
- support vector
- resource allocation
- learning tasks
- multiple classifier systems
- learning algorithm
- learning classifier systems
- training data
- statistical tests
- inductive learning
- classification algorithm
- support vector machine
- imbalanced data
- data mining
- active learning
- random sampling
- svm classifier
- training samples
- test data
- naive bayes
- training set
- sampling methods
- file organization
- roc analysis
- training examples
- training stage
- classification models
- order preserving
- ensemble learning
- random projections
- test cases
- sample size
- feature ranking
- minority class
- semi supervised learning
- dimensionality reduction
- ensemble methods
- natural language processing
- supervised learning