Evaluating and Comparing Heterogeneous Ensemble Methods for Unsupervised Anomaly Detection.
Simon KlüttermannEmmanuel MüllerPublished in: IJCNN (2023)
Keyphrases
- ensemble methods
- unsupervised anomaly detection
- anomaly detection
- prediction accuracy
- benchmark datasets
- ensemble learning
- random forests
- machine learning methods
- decision trees
- base classifiers
- majority voting
- semi supervised
- drifting concepts
- intrusion detection
- bootstrap sampling
- generalization ability
- base learners
- classifier ensemble
- unsupervised learning
- machine learning
- random forest
- feature subset
- ensemble feature selection
- real world
- feature selection
- classification accuracy