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i'm studying with you website,
https://cienciadedatos.net/documentos/py53-global-forecasting-models.html
there are more than 1000 buildings.
when i resample building with
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### pycaret version checks
- [X] I have checked that this issue has not already been reported [here](https://github.com/pycaret/pycaret/issues).
- [X] I have confirmed this bug exists on the [la…
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Currently `ForecastMultiSeriesCustom` and `ForecastMultiSeries` implement a recursive approach to multi-series forecasting. `ForecastMultiVariate` implements a direct forecasting approach for multivar…
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**Is your feature request related to a current problem? Please describe.**
Training a global forecasting model that uses `LightGBM` on a relatively large dataset, and then saving the resulting trai…
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Hello there, there are a few other approaches to this that I have seen and wondered if they are on your radar.
Bellman Conformal Inference (BCI) - optimises prediction intervals for time series …
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**Describe the bug**
After training a TFT with `ddp_spawn`strategy on multiple gpus in Amazon SageMaker the returned prediction of the trainer is None, leading to an `TypeError: 'NoneType' object is …
nejox updated
2 months ago
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Darts has established itself as a premier time series forecasting library. Adding multi-horizon time series classification support would solidify its position and significantly benefit researchers and…
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reference: https://machinelearningmastery.com/how-to-develop-lstm-models-for-multi-step-time-series-forecasting-of-household-power-consumption/
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* 논문제목 : Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting
* 분야 : time series
* 논문 링크 : https://arxiv.org/pdf/1912.09363.pdf
* 발표 자료 : https://cottony-wedelia-967…
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For the API design proposal, see [this wiki entry](https://github.com/alan-turing-institute/sktime/wiki/Forecasting-API-proposal).
## Forecasters
### Atomic
- [x] NaiveForecaster (strategies={"l…