Litcius/Paper detail

Self-adjusting <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si9.svg"><mml:mrow><mml:mi>k</mml:mi></mml:mrow></mml:math> nearest neighbors for continual learning from multi-label drifting data streams

Martha Roseberry, Bartosz Krawczyk, Youcef Djenouri, Alberto Cano

2021Neurocomputing39 citationsDOI

Topics & Concepts

Computer scienceData stream miningRobustness (evolution)Data streamConcept driftArtificial intelligenceAlgorithmMachine learningData miningPattern recognition (psychology)ChemistryTelecommunicationsBiochemistryGeneData Stream Mining TechniquesMachine Learning and Data ClassificationText and Document Classification Technologies
Self-adjusting <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si9.svg"><mml:mrow><mml:mi>k</mml:mi></mml:mrow></mml:math> nearest neighbors for continual learning from multi-label drifting data streams | Litcius