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Update mlforecaster.md
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davidusb-geek authored Dec 19, 2023
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Expand Up @@ -16,13 +16,13 @@ To train a model use the `forecast-model-fit` end point.

Some paramters can be optionally defined at runtime:

- `days_to_retrieve`: the total days to retrieve from Home Assistant for model training. Defined this in order to retrieve as much history data as possible.
- `days_to_retrieve`: the total days to retrieve from Home Assistant for model training. Define this in order to retrieve as much history data as possible.

```{note}
The minimum number of `days_to_retrieve` is hard coded to 9 by default. But it is adviced to provide more data for better accuracy by modifying your Home Assistant recorder settings.
```

- `model_type`: define the type of model forecast that this will be used for. For example: `load_forecast`. This should be an unique name is you are using multiple custom forecast models.
- `model_type`: define the type of model forecast that this will be used for. For example: `load_forecast`. This should be an unique name if you are using multiple custom forecast models.

- `var_model`: the name of the sensor to retrieve data from Home Assistant. Example: `sensor.power_load_no_var_loads`.

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