v0.13.0

Breaking Change

• set refit=False and results_ as dict in AutoMLForecast @jmoralez (#341)

Bug fixes

• fix: fitted nonrecursive cv with horizon >= 10 @adriaanvh1 (#333)

Enhancement

• speedup date features @jmoralez (#340)
• Create CODE_OF_CONDUCT.md @tracykteal (#335)

v0.12.1

New Features

• add auto module for hyperparameter optimization @tblume1992 (#306)
• add DistributedMLForecast.update @jmoralez (#324)

Bug Fixes

• fix cv fitted values with prediction intervals @jmoralez (#330)

v0.12.0

Enhancement

• migrate to coreforecast @jmoralez (#311)

v0.11.8

Bug Fixes

• ensure coreforecast is installed for AutoDifferences @jmoralez (#314)

v0.11.7

New Features

• add auto differences @jmoralez (#310)

v0.11.6

New Features

• add to_local method to distributed forecast @jmoralez (#302)
• support saving and loading forecast objects @jmoralez (#301)

v0.11.5

Bug Fixes

• add update method to target_transforms @jmoralez (#293)

Enhancement

• use coreforecast target_transforms when installed @jmoralez (#294)

v0.11.4

Bug Fixes

• fix predict with multiple models @jmoralez (#290)

Dependencies

• polars updates @jmoralez (#291)

v0.11.3

New Features

• add level argument to forecast_fitted_values @jmoralez (#287)
• add X_df argument to distributed predict @jmoralez (#286)

v0.11.2

New Features

• add X_df debugging methods @jmoralez (#283)
• add quantile lag_transforms @jmoralez (#282)
• support lag transforms namer @jmoralez (#280)

Documentation

• add sklearn pipelines guide @jmoralez (#277)

Dependencies

• update utilsforecast @jmoralez (#281)

Enhancement

• don't recompute features already present in df @jmoralez (#279)