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### Description
`mlforecast` currently allows for recursive single-model forecasts, or direct multi-model forecasts where a single model is trained to predict a particular data point in the horizon…
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Someone can explain to me how to make inference using a trained model using the code in timeseries_traffic_forecasting.py?
Imagine that a have historical data from 45 timesteps for 33 roads, and th…
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Current Status/Forecasting:
- [x] Number ongoing now
- [ ] Number expected to start within next 3 months (maybe allow for the months to vary)
- [x] Number comprehensive consul…
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Hi,
First of all thanks for putting this ARIMA summary online.
Second, I have a question. How would someone make predictions on the future (test set) if observed data are still unknown (NaN). Here is…
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**Is your feature request related to a problem?**
This is a container to house forecasting feature requirements as they progress.
**What solution would you like?**
[Proposal](https://github.com/o…
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As this relies on the BSTS methodology, is there a way to use tfcausalimpact for forecasting alone, i.e. setting the post-period to values beyond the final timestamp of the available data? R BSTS of c…
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In the TFT branch, is there a reason why the multi-class is not activated? After looking at the code, it seems that the model itself can handle it. Thus, beside removing the lines throwing error and u…
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Hi,
I saw in the paper that you experiment on the Tracking split of Argoverse dataset. I thought the common split people use for trajectory forecasting is the motion forecasting split of Argoverse…
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Demonstrate Traja with a stock market price forecasting example.
Good place to start is the Colab notebook: https://colab.research.google.com/github/justinshenk/traja/blob/master/demo.ipynb