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@mikekeith52
Created June 7, 2022 23:03
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selected_model = "gbt"
hp = results[selected_model][3]
f.set_estimator(selected_model)
f.manual_forecast(**hp, Xvars="all", call_me=selected_model + "_all_vars")
f.manual_forecast(
**hp, Xvars=lasso_reduced_vars, call_me=selected_model + "_l1_reduced_vars"
)
f.manual_forecast(
**hp, Xvars=mlr_reduced_vars, call_me=selected_model + "pfi-mlr_reduced_vars"
)
f.manual_forecast(
**hp, Xvars=knn_reduced_vars, call_me=selected_model + "pfi-knn_reduced_vars"
)
f.manual_forecast(
**hp, Xvars=gbt_reduced_vars, call_me=selected_model + "pfi-gbt_reduced_vars"
)
f.manual_forecast(
**hp, Xvars=svr_reduced_vars, call_me=selected_model + "pfi-svr_reduced_vars"
)
export_results(f)
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