v0.13.4

New Features

• feat: mlflow flavor @jmoralez (#406)

Documentation

• Clear up the README for the new user @Ammar-Azman (#397)

Enhancement

• make season_length optional in AutoMLForecast @jmoralez (#399)

v0.13.3

Bug Fixes

• handle no target transforms in DistributedMLForecast.to_local @jmoralez (#388)

Enhancement

• ensure static features are constant @jmoralez (#391)

v0.13.2

New Features

• support prediction intervals in auto @jmoralez (#370)

Bug Fixes

• remove dots from feature names in distributed @jmoralez (#382)
• fix min_samples_split in random forest space @jmoralez (#380)

Enhancement

• store prediction intervals inputs in MLForecast.save @jmoralez (#383)
• support polars in GlobalSklearnTransformer @jmoralez (#377)

v0.13.1

Dependencies

• add polars extra @jmoralez (#368)
• support polars 1.0 @jmoralez (#366)

Enhancement

• add fitted argument to AutoMLForecast.fit @jmoralez (#351)

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)