Abstract
AbstractIn this chapter, we discuss two more advanced methods, which are recent advancements in demand prediction. We first present the Prophet method, which is an open-sourced library released by Facebook researchers in 2017. Prophet is a time-series demand prediction method that often performs well on large-scale problems. We explain the method and discuss its implementation both with and without incorporating features. We then present a method that can strike a good balance between data aggregation (i.e., finding the right data granularity level) and demand prediction accuracy. We present the method, discuss how to fine-tune its hyperparameters, and conclude by interpreting the results obtained on the accompanying dataset.
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