A Knowledge Extraction Pipeline between Supervised and Unsupervised Machine Learning Using Gaussian Mixture Models for Anomaly Detection.
Reda ChefiraSaid RakrakPublished in: J. Comput. Sci. Eng. (2021)
Keyphrases
- anomaly detection
- knowledge extraction
- unsupervised learning
- machine learning
- supervised learning
- supervised classification
- unsupervised anomaly detection
- knowledge discovery
- data mining
- semi supervised
- intrusion detection
- novelty detection
- network anomaly detection
- anomalous behavior
- detecting anomalies
- learning algorithm
- network intrusion detection
- unsupervised methods
- network traffic
- feature selection
- network security
- computer security
- active learning
- detecting anomalous
- model selection
- behavior analysis
- one class support vector machines
- text classification
- intrusion detection system
- decision trees
- object recognition
- pattern recognition
- self organizing maps
- information extraction
- computer vision
- expectation maximization
- dimensionality reduction
- detect anomalies
- negative selection algorithm
- connectionist systems
- malware detection
- fuzzy logic
- support vector machine
- data analysis
- training data