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modeling docs

The model training and visualization pipeline lives in: modeling/basic_model_framework.ipynb which will train and visualize the outputs of various models.

The high level wrapper for training and predicting values is the fit_and_predict function in modeling/fit_and_predict.py this allows you to train a few models by passing in different arguments. For more details please see the function documentation.

To simply get the predictions for the best model, use the add_preds function:

from fit_and_predict import add_preds
df = add_preds(df, NUM_DAYS_LIST=[1, 3, 5]) # adds keys like "Predicted Deaths 1-day", "Predicted Deaths 3-day"
# NUM_DAYS_LIST is list of number of days in the future to predict

reproducibility

  • to reproduce all the results in the paper, first run predict_all_deaths.py and then run reproduce_paper_results.py