Model: MIT-CriticalData - MIT_CritData-GBCF

    Name: Gradient Boosted COVID Forecaster (GBCF)
    Abbreviation: MIT_CritData-GBCF
    Owner: covid19hub
    Team name: MIT-CriticalData
    Description: This gradient boosted regressor model with hyperparameter optimization is trained on prior COVID metrics as well as demographic, socioeconomic, mobility, and health-related county-level covariates.
    Contributors: Nicolas Della Penna (LCP at MIT, Amurado Research OU) <nikete@mit.edu>, Saketh Sundar<sakethsundar2009@gmail.com>, Leo A. Celi(LCP at MIT) <leoanthonyceli@yahoo.com>
    License: MIT
    Notes: primary
    Citation: Missing
    Methods: This model uses a gradient boosted regressor with hyperparameter optimization that uses prior COVID cases and deaths as well as demographic, socioeconomic, mobility, and healthcare related county-level covariates. This model forecasts COVID deaths at the county level and aggregates to the state and national level. This model does not directly account for state reopenings and closures but indirectly via changes in the mobility measures.
    Home: https://github.com/sakethsundar/covid-forecaster
    Auxiliary data: Missing

    Forecasts (8)

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