Feat/CatBoost model

[jonasracine]

• Added Catboost regression model. Currently, supports same probabilistic prediction possibilities (quantile and poisson) as Dart's LGBM implementation.

• The Catboost class is mostly a copy-paste of the LGBM class.
  Question: should this be refactored to avoid code duplication?

• Future work: add support for Catboost's own "RMSEWithUncertainty" loss function, that returns [mean, variance] (see https://towardsdatascience.com/tutorial-uncertainty-estimation-with-catboost-255805ff217e)

[codecov-commenter]

Codecov Report

Attention: Patch coverage is 94.54545% with 3 lines in your changes missing coverage. Please review.

Project coverage is 91.33%. Comparing base (8eb331a) to head (6060bf4).
Report is 467 commits behind head on master.

Files with missing lines	Patch %	Lines
darts/models/forecasting/catboost_model.py	94.44%	3 Missing ⚠️

Additional details and impacted files

@@           Coverage Diff           @@
##           master    #1007   +/-   ##
=======================================
  Coverage   91.32%   91.33%           
=======================================
  Files          77       78    +1     
  Lines        7876     7917   +41     
=======================================
+ Hits         7193     7231   +38     
- Misses        683      686    +3     

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

[hrzn]

Thanks @jonasracine , it looks like a good start.
Could you add unit tests?
Concerning factoring out the code, I think it's not necessary at the moment (we can do it later if we have more similar models coming).
Finally, how much work is it to add the RMSE mu/sigma version? It's probably not too difficult I imagine, in which case I'd vote for making it part of this PR.

[hrzn]

@jonasracine there are ~60 .coverage files committed too :) could you remove them?

[hrzn]

LGTM, thanks