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GP module #151

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choltz95 opened this issue Sep 27, 2019 · 2 comments · May be fixed by #241
Open

GP module #151

choltz95 opened this issue Sep 27, 2019 · 2 comments · May be fixed by #241
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@choltz95
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choltz95 commented Sep 27, 2019 •
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Support for gaussian process may be a great addition to this library
e.g. normalizing sparse/irregular time series, uncertainty estimation, etc..

Regression/classification can probably be easily done similarly to the svm/svc module using sklearn, but here is an example of a more sophisticated gp library for inspiration: https://github.com/cornellius-gp/gpytorch
@rtavenar
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Hi @choltz95

100% agree.

I also think that more traditional stat models, like linear auto regressive and co would be great to have in future tslearn releases.

@choltz95 choltz95 mentioned this issue Jan 3, 2020
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@choltz95
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choltz95 commented Jan 3, 2020 •
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Not going to make a new issue, but it's seems natural if GPs are included in the library to maybe also have some api for HMMs.

@rtavenar rtavenar linked a pull request May 23, 2020 that will close this issue
[WIP] Compatibility with sklearn's GPR module #241
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[WIP] Compatibility with sklearn's GPR module choltz95/tslearn
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