Automatic vs. manual feature engineering for anomaly detection of drinking-water quality.
Valerie FehstHuu Chuong LaTri-Duc NghiemBen E. MayerPaul EnglertKarl-Heinz FiebigPublished in: GECCO (Companion) (2018)
Keyphrases
- anomaly detection
- water quality
- feature engineering
- intrusion detection
- dependency parsing
- anomalous behavior
- detecting anomalies
- network traffic
- water treatment
- network anomaly detection
- network intrusion detection
- one class support vector machines
- intrusion detection system
- detecting anomalous
- text classification
- measured data
- machine learning
- negative selection algorithm
- unsupervised learning
- natural language processing
- detect anomalies
- labeled data
- signal processing
- hidden markov models
- object recognition
- real world
- data sets