Improve usability for conditional seasonality #1116
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* Quarterly changing weekly seasonality
* On-season and off-season football * Adapted from Facebook Prophet
judussoari
added
type:docs
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## main #1116 +/- ##
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+ Coverage 90.16% 90.17% +0.01%
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Files 36 36
Lines 5042 5059 +17
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+ Hits 4546 4562 +16
- Misses 496 497 +1
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judussoari
changed the title
judussoari
added
status: blocked
and removed
status: needs review
Model Benchmark
Model training plotsModel TrainingPeytonManningYosemiteTempsAirPassengers |
…ndition to the dataframe
…ndition to the dataframe
judussoari
added
status: needs review
|
@ourownstory when you or someone else review this, please have a look at the new helper function with the pre-implmented conditional seasonalities, and evaluate whether it makes sense |
* when missing dates are added * when predicting (ffill at end)
* when missing dates are added * when predicting (ffill at end)
* when missing dates are added * when predicting (ffill at end)
* when missing dates are added * when predicting (ffill at end)
* when missing dates are added * when predicting (ffill at end)
ourownstory
previously requested changes
Feb 8, 2023
neuralprophet/forecaster.py
Outdated
| -------- | ||
| Adding a quarterly changing weekly seasonality to the model. First, add columns to df. | ||
| The columns should contain only zeros and ones (or floats), deciding when to apply seasonality. | ||
| >>> df["summer_week"] = df["ds"].apply(lambda x: x.month in [6, 7, 8]) |
judussoari
added
status: ready
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🔮 Key changes
Extends #1067
Added docstring example, a new tutorial notebook for conditional seasonality, as well as some validation for float values between 0..1 in the conditional seasonality column.
Also, added helper function to integrate four seasons and/or weekday/weekend conditions. Fixes #609
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