A data-driven interpretable ensemble framework based on tree models for forecasting the occurrence of COVID-19 in the USA
Hu-Li Zheng, Shu-Yi An, Baojun Qiao, Peng Guan, Desheng Huang, Wei Wu
Topics & Concepts
InterpretabilityRandom forestGradient boostingEnsemble learningMachine learningEnsemble forecastingArtificial intelligenceDecision treeBoosting (machine learning)Computer scienceTree (set theory)Data miningStatisticsMathematicsMathematical analysisCOVID-19 epidemiological studiesCOVID-19 diagnosis using AICOVID-19 Clinical Research Studies