The preceding chapter covered seasonal ARIMA. After all the considerable effort in data preprocessing and hyperparameter optimization, the model generates considerable errors when forecasting future instances of the series. For a fast and automated forecasting procedure, use Facebook’s Prophet; it forecasts time-series data based on nonlinear trends with seasonality and holiday effects. This chapter introduces Prophet and presents a way of developing and testing an additive model. First, it discusses ...
© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2021
T. C. NokeriData Science Revealedhttps://doi.org/10.1007/978-1-4842-6870-4_44. High-Quality Time-Series Analysis
Tshepo Chris Nokeri1
(1)
Pretoria, South Africa
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