Common time series dataset to facilitate model training and evaluation

[ben-jy]

When evaluating different models, datasets and their parameters may slightly differ. It would be beneficial to have a common dataset class that allows to define the important parameters for constructing a dataset, i.e. :

• the covariate components (if needed, past, future, static, etc.)
• the target components (components we must predict)
• the split (train-val-test)
• normalization
• ...

[ben-jy]

we already have a “BenchmarkDataset” class that seems to cover most of the points listed above. Why would we need another dataset class?

[ben-jy]

we already have a “BenchmarkDataset” class that seems to cover most of the points listed above. Why would we need another dataset class?

Some model implementations, such as Moirai e.g., can receive specific parameters for their fit/predict methods that might improve quality of prediction, such as covariate, static features, etc.
We must find a way to give these parameters in a common way across models, that is why this issue was created. With a new time series inheriting from onTime TimeSeries object, we could give this information, and model could check on them.
Still, maybe we can find another way to perform this.