Litcius/Paper detail

SDDM: an interpretable statistical concept drift detection method for data streams

Simona Micevska, Ahmed Awad, Sherif Sakr

2021Journal of Intelligent Information Systems30 citationsDOI

Topics & Concepts

Concept driftComputer scienceData stream miningClassifier (UML)Data streamFalse positive paradoxDetectorBinary classificationArtificial intelligenceData miningBinary numberFalse positives and false negativesChange detectionMachine learningPattern recognition (psychology)Support vector machineMathematicsArithmeticTelecommunicationsData Stream Mining TechniquesAnomaly Detection Techniques and ApplicationsMachine Learning and Data Classification
SDDM: an interpretable statistical concept drift detection method for data streams | Litcius