add RMSE and MAE metrics.
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3845). All of your documentation changes will be reflected on that endpoint. @mariosasko I've reopened it here. Please suggest any changes if required. Thank you. Thanks for suggestions. :) I have added update the KWARGS_DESCRIPTION for the missing params and also changed RMSE to MSE.
While testing, I noticed that when the input is a list of lists, we get an error :
`TypeError: float() argument must be a string or a number, not 'list'`
Could you suggest the datasets.Value() attribute to support both list of floats and list of lists containing floats ?
 Just add a new config to cover that case. You can do this by replacing the current `features` dict with:
```python
features=datasets.Features(
    {
        "predictions": datasets.Sequence(datasets.Value("float")),
        "references": datasets.Sequence(datasets.Value("float")),
    }
    if self.config_name == "multioutput"
    else {
        "predictions": datasets.Value("float"),
        "references": datasets.Value("float"),
     }
),
```
Feel free to suggest a better name for the config than `multioutput` Also, could you please move the changes to a new branch and open a PR from there (for the 3rd time 😄) because the diff shows changes from unrelated PRs (maybe due to rebasing?). Thanks for the input, I have added new config to support multi-dimensional lists and updated the examples as well.

Sure. Will do that and open a new PR for these changes.
This PR adds RMSE - Root Mean Squared Error and MAE - Mean Absolute Error to the metrics API.
Both implementations are based on usage of sciket-learn.

Feature request here : Add support for continuous metrics (RMSE, MAE) [#3608](https://github.com/huggingface/datasets/issues/3608)

Please suggest any changes if required. Thank you.