[Feature request] time series classification
Aceticia opened this issue · 2 comments
Theoretically this should be compatible with the encoder - decoder style framework we have here?
Alternatively, adding a method that returns the extracted features after a forecasting model is trained.
Thanks for the suggestion,
Unfortunately, we are busy with some other work these days and may add this feature in the near future.
However, here are some hints:
you could write a new pipeline for time series classification, which should be something similar to the tabular classification pipline and reimplement the [classification network] (https://github.com/automl/Auto-PyTorch/blob/master/autoPyTorch/pipeline/components/setup/network/base_network.py), adding them to the pipeline.
Additionally, the network backbone might also need to be modified accordingly: Auto-regressive needs to be removed.
Then you need to create a new class for time series classification task that is inherent from this class. Then everything should work as expected