RADE: resource-efficient supervised anomaly detection using decision tree-based ensemble methods.
Shay VargaftikIsaac KeslassyAriel OrdaYaniv Ben-ItzhakPublished in: Mach. Learn. (2021)
Keyphrases
- anomaly detection
- ensemble methods
- intrusion detection
- detecting anomalies
- unsupervised learning
- network traffic
- anomalous behavior
- random forests
- network intrusion detection
- prediction accuracy
- decision trees
- machine learning methods
- intrusion detection system
- network anomaly detection
- detect anomalies
- ensemble learning
- semi supervised
- one class support vector machines
- bootstrap sampling
- multiple models
- data mining
- base classifiers
- data mining applications
- benchmark datasets
- supervised learning
- pairwise
- pattern recognition
- image processing