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Description
While I'm here, I wanted to point out that at sktime, we've started to interface pyts algorithms, upon popular demand, to have them indexed for users who are searching for TSC and time series transformations.
Users will be able to find interfaced estimators using the indexing utility all_estimators in sktime.registry, and use them as components in sktime pipelines and composites. For this, users will need to install pyts, and they recieve an informative error message to this effect when they attempt to construct pipelines. Proper credit to pyts is of course also given, by name of estimator (uses pyts brand) and in docstring, feedback appreciated.
The estimators are also regularly tested against standard API contracts, that's how we found #158.
If you would like to help out, or observe:
- issue on
sktimeis here, feel free to comment: [ENH] interfacingpytsestimators sktime/sktime#5850 - adding new
pytsestimators is formulaic, we have written a general adapter that can be inherited from
We're not sure yet about distances.
Further, the knn classifier is neat, but we're wondering what is the best way to allow it to take abstract distances, which are first order citizens in sktime (also estimators). Perhaps there is a collaboration opportunity here.