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that has multiple seasonality with linear or non-linear growth. Submitted by: Gilbert Morgan <gmm@tutanota.com> (via private email)
8 lines
424 B
Text
8 lines
424 B
Text
Implements a procedure for forecasting time series data based on an additive
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model where non-linear trends are fit with yearly, weekly, and daily
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seasonality, plus holiday effects. It works best with time series that have
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strong seasonal effects and several seasons of historical data. Prophet is
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robust to missing data and shifts in the trend, and typically handles outliers
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well.
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WWW: https://github.com/facebook/prophet
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