StructuralTime Series
DescriptionVisualization
StructuralTime Series isthe
decompositionofthedatain at least:
Data Seasonality
Trend Exogenousimpacts
Methodologicalframework
Trend
Seasonality
Exogenousimpacts
Error Term
Facebook Prophet quick facts
Which?
Description
Prophet is customizable in ways that are intuitive to
non-experts
4
Stan background-probabilisticprogramming
languageforstatisticalinference
2
Builtbyfacebook1
Dynamic Holidays3
Built-in Cross Validation5
Facebook Prophet Model
DescriptionComponent
HolidaysHolidays Dataframe thatwepreparedDataframe thatweprepared
SeasonalitySeasonality Yearly, weeklyordaily. True orFalseYearly, weeklyordaily. True orFalse
Seasonality_modeSeasonality_mode MultiplicativeoradditiveMultiplicativeoradditive
Seasonality_prior_scaleSeasonality_prior_scale Strength of the seasonalityStrength of the seasonality
Holiday_prior_scaleHoliday_prior_scale Larger values allow the model to fit larger seasonal fluctuationsLarger values allow the model to fit larger seasonal fluctuations
Changepoint_prior_scaleChangepoint_prior_scale Does the Trend change easily?Does the Trend change easily?
Pros and Cons
Can needintenseoptimization
2
Not goodwithshort-term dynamics
3
Complexprogramming
1
Flexible
1
Built-in Cross Validation
2
Dynamics Events
3
Great withRegressors
4
Challenge
A Dataset withDaily UdemyWikipedia Visits
Description
PredictthenumberofvisitstotheWikipedia pageof
Udemy
1
Set Easter and Christmas aseventsand Black
Friday asRegressor
2
Visualizeresults3
Measureaccuracy4
Test Set mustbe31 days5