Open fkiraly opened 5 months ago
Thank you. I am going to look into this!
So, any thoughts? We could have a short call if you´d like.
I'd like to patricipate but due high workload in June, I can't work at this a lot (I can probably take some small tasks).
In Jule I'll be able to actively work on distfit
refactoring.
I suggest the following way:
I'm going to try to analyse the current state of code ASAP, but I'm not sure on the time again..
@erdogant, I was wondering whether you would be interested to actively contribute to integration with
sktime
andskpro
? https://github.com/sktime/sktime https://github.com/sktime/skprosktime
is currently the most widely used sklearn-like framework package for time series.skpro
is an similar project around tabular modelling with probability distributions, such as tabular supervised probabilistic regression, or conditional density/distribution estimation. It integrates withsktime
, for things like probabilistic forecasting.distfit
would fit nicely, as its distribution estimation capabilities are broad, and provide some required components for things like anomaly detction - tabular and time series - and probabilistic regression. For instance, one could imagine it being used as the probability estimating component in a probabilistic forecaster.I was planning a simple interfacing (which you're welcome to review or contribute to), but we could consider closer integration, I'd be happy to contribute, for instance:
distfit
towards more object oriented structure andscikit-learn
like interface, similar toskpro.distributions
which is usingskbase
for ansklearn
-like interface for distributions. I believe this is also the same that @roman223 is suggesting in https://github.com/erdogant/distfit/issues/44skpro
native distributions, ensuring we sync the large collection of distributions available indistfit
,scipy
, with an object oriented interface like inskpro
. We may have to redesign some aspects of it so it satisfies your requirements for fitting.What do you think?
I am not sure of the best way to chat, but you are cordially invited to the
sktime
discord and its channels dedicated to probability modelling: https://discord.com/invite/54ACzaFsn7