How does Prophet work? Part-1
So every time we think of implementing Time Series Modelling, The first few libraries that come to our mind are — Either Regression, ARIMA or Prophet. But do we know what is happening in the background of these algorithms and how can we further tune them to make it work for out time-series dataset —
Prophet Forecasting Model — It is an Additive Regressive Model
Equation of the model is —
Let’s understand these components in little depth —
In this post, I Will focus on Tuning of Trend factor. In my next post, I will share how to tune seasonality and other components of the prophet.
g(t) — Trend Factor — It implements two possibles trend models
a) Logistic growth model — It handles non-linear growth with saturation ( you might be wondering what does it mean now? uh .. confused ??) Let’s understand —
Non-linear growth with saturation — The initial stage of growth is approximately exponential (geometric), as saturation begins, the growth slows to linear (arithmetic) and at maturity, growth stops.
