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Source allocation of per- and polyfluoroalkyl substances (PFAS) with supervised machine learning: Classification performance and the role of feature selection in an expanded dataset

Tohren C. G. Kibbey, Rafal Jabrzemski, Denis M. O’Carroll

2021Chemosphere46 citationsDOI

Topics & Concepts

PreprocessorFeature selectionComputer scienceIdentification (biology)Artificial intelligenceMachine learningSelection (genetic algorithm)Sample (material)Feature (linguistics)ChemistryEcologyChromatographyBiologyPhilosophyLinguisticsPer- and polyfluoroalkyl substances researchToxic Organic Pollutants ImpactAtmospheric chemistry and aerosols
Source allocation of per- and polyfluoroalkyl substances (PFAS) with supervised machine learning: Classification performance and the role of feature selection in an expanded dataset | Litcius