Discovering boundary values of feature-based machine learning classifiers through exploratory datamorphic testing.
Hong ZhuIan BayleyPublished in: J. Syst. Softw. (2022)
Keyphrases
- machine learning
- machine learning methods
- machine learning algorithms
- machine learning approaches
- decision trees
- feature selection
- training data
- supervised classification
- test set
- supervised learning
- svm classifier
- support vector
- pattern recognition
- parameter values
- semi supervised learning
- neural network
- classification systems
- feature values
- feature set
- inductive learning
- object boundaries
- naive bayes
- learning tasks
- roc analysis
- test data
- meta learning
- linear classifiers
- multiple classifiers
- multiple classifier systems
- data mining
- training examples
- learning algorithm
- training samples
- text classification
- computer vision
- attribute values
- reinforcement learning
- knowledge representation
- training stage
- artificial intelligence
- explanation based learning
- computer science
- active learning
- text mining
- statistical tests
- text categorization
- learning problems
- test cases