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Merge pull request #49 from nfidd/edit-closing
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Edits to closing talk
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seabbs authored Nov 5, 2024
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- forecast visualisation (session 1)
- forecast evaluation (session 2)
- forecast ensembles (sesion 3)
- forecast evaluation of multiple models (session 3)
- forecast ensembles (session 4)

# Key takeaways

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### Session 3: Forecast ensembles

- forecasts can combine **forecasts from multiple models**
- simple ensembles often outperform indivdiual models
- simple ensembles often outperform individual models
- weighted ensembles can learn from past performance aiming to make better forecasts

### Outlook {.smaller}

- it is worth trying some of these methods here in practice to learn more about typical forecast performance
- one way of doing so is by contributing to forecast hubs

![](figures/respicast.png)
![](figures/respicast-forecasts.png)

[https://respicast.ecdc.europa.eu/](https://respicast.ecdc.europa.eu/)

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