Machine Learning Techniques for Improving Multiclass Anomaly Detection on Conveyor Belts.
Saulo N. MatosOtávio Ferracioli ColettiRafael ZimmerFernando Ugucioni FilhoRicardo C. C. L. de CarvalhoVictor R. da SilvaJorge L. FrancoThomás V. B. PintoLuiz Guilherme Dias de BarrosCaetano Mazzoni RanieriBruno Eduardo LopesDiego F. SilvaJó UeyamaGustavo PessinPublished in: I2MTC (2024)
Keyphrases
- anomaly detection
- multi class
- intrusion detection
- detecting anomalies
- anomalous behavior
- network intrusion detection
- intrusion detection system
- network traffic
- network anomaly detection
- multiclass classification
- pairwise
- multiclass problems
- one class support vector machines
- feature selection
- cost sensitive
- binary classifiers
- machine learning algorithms
- support vector machine
- machine learning methods
- binary classification
- unsupervised learning
- detect anomalies
- multiclass support vector machines
- negative selection algorithm
- multiclass learning
- perceptron algorithm
- error correcting output codes
- normal behavior
- multiple classes
- multi task
- machine learning
- binary classification problems
- kernel function
- maximum likelihood
- learning algorithm
- neural network