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Gradient Boosted ARIMA for Time Series Forecasting
Boosting PmdArima’s Auto-Arima performanceImage by SpaceX on Unsplash
TLDR: Adding gradient boosting to ARIMA adds complexity to the fitting procedure but can also drive accuracy if we optimize for new (p,d,q) parameters at each boosting round. Although, more gains can be achieved by boosting in conjunction with other methods.
All code lives here: ThymeBoost Github
For a full introduction to ThymeBoost view this article.
Gradient Boosting has been a hot topic in the machine learning world for …