Abstract: For a time-series, a baseline error value is reduced to compute a target forecast error value by maximizing a net benefit value of a forecasted value of the time-series. For each forecasting model in a set of models, a corresponding model error value related to the time-series is computed. From the set, a subset of models is selected where each model in the subset has a cost that will produce a positive value for the net benefit. A selected model from the subset is associated with the time-series such that a model error value of the selected model is at most equal to the target forecast error. The time-series is forecasted using the selected model such that the forecasted value has an error of less than the baseline error at a future time, and the forecasted value produces a positive net benefit at the future time.

Abstract: For a time-series, a baseline error value is reduced to compute a target forecast error value by maximizing a net benefit value of a forecasted value of the time-series. For each forecasting model in a set of models, a corresponding model error value related to the time-series is computed. From the set, a subset of models is selected where each model in the subset has a cost that will produce a positive value for the net benefit. A selected model from the subset is associated with the time-series such that a model error value of the selected model is at most equal to the target forecast error. The time-series is forecasted using the selected model such that the forecasted value has an error of less than the baseline error at a future time, and the forecasted value produces a positive net benefit at the future time.