Effective subgrouping enhances machine learning prediction in complex materials science phenomena: Inoue's subgrouping in discovering bulk metallic glasses
Liu G, Sohn S, O'Hern C, Gilbert A, Schroers J. Effective subgrouping enhances machine learning prediction in complex materials science phenomena: Inoue's subgrouping in discovering bulk metallic glasses. Acta Materialia 2024, 265: 119590. DOI: 10.1016/j.actamat.2023.119590.Peer-Reviewed Original ResearchMaterials science problemsScience problemsPhysical insightStatistical methodsMetallic glass formationMaterials discoveryGlass formationMachine learningML modelsHigh prediction accuracyProblem spacePrediction accuracyProblemScience phenomenaML strategiesMetallic glassesMaterials science phenomenaGlass-forming abilityComposition-property relationshipsModelSpaceWide rangePhenomenonEntire datasetRepresentation