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Semi-supervised anomaly detection algorithms: A comparative summary and future research directions

Miryam Elizabeth Villa-Pérez, Miguel Á. Álvarez‐Carmona, Octavio Loyola‐González, Miguel Angel Medina‐Pérez, Juan Carlos Velazco-Rossell, Kim‐Kwang Raymond Choo

2021Knowledge-Based Systems137 citationsDOI

Topics & Concepts

Anomaly detectionSupport vector machineComputer scienceBenchmark (surveying)Classifier (UML)One-class classificationArtificial intelligenceMachine learningAnomaly (physics)Pattern recognition (psychology)Focus (optics)Data miningGeographyPhysicsCondensed matter physicsGeodesyOpticsAnomaly Detection Techniques and ApplicationsNetwork Security and Intrusion DetectionData-Driven Disease Surveillance
Semi-supervised anomaly detection algorithms: A comparative summary and future research directions | Litcius