v0.3.1

Changed

• Added upper bound <0.24.0 for scikit-learn version (#59)

v0.3.0

Changed

• Fix dependencies to make stacking compatible with scikit-learn 0.23+ (#54)
• Removed support for Python <3.6. (#55)

v0.2.1

[0.2.1] - 2020-01-15

Changed

• Make stacking compatible with scikit-learn v0.22.1. (#52)

v0.2.0

Added

• Turn on Python 3.7 and 3.8 for Travis CI builds. (#50)

Changed

• Removed the upper version bound for sklearn. (#50)
• Update tests and requirements.txt to allow sklearn 0.20 and above. (#47)
• Instead of boolean flag for dummy_na, have None/False (no dummying),
  'expanded' (matches previous True behavior), and 'all' (dummy NAs
  in all columns where they appear, not just ones we're categorically
  expanding). (#44)

[0.1.10] - 2019-01-16

Added

• Raise a RuntimeError if there are more than 5000 levels in a column (#42)
• Emit a warning if the column levels during transform don't overlap at all with levels from fitting (#41)

v0.1.9

[0.1.9] - 2018-05-17

Fixed

• In DataFrameETL, don't check for levels to expand in columns which
  are slated to be dropped. This will avoid raising a warning for too
  many levels in a column if the user has intentionally excluded
  that column (#39).

v0.1.8

[0.1.8] - 2018-04-19

Fixed

• Fixed DataFrameETL transformations of DataFrames with non-trivial
  index when preserving DataFrame output type (#32, #33)
• Add pandas version restrictions by Python version (#37)
• Fix code which was incompatible with older pandas version (#37)

v0.1.7

[0.1.7] - 2018-03-27

Added

• Added debug log emits for the DataFrameETL transformer (#24, #27)
• Added debug log emits for the HyperbandSearchCV estimator (#28, #29)
• Emit a warning if the user attempts to expand a column with
  too many categories (#25, #26)

[0.1.6] - 2018-1-12

Fixed

• Now caching CV indices. When CV generators are passed with shuffle=True and
  no random_state is set, they produce different CV folds on each call to
  split (#22).
• Updated scipy dependency in requirements.txt file to scipy>=0.14,<2.0
• DataFrameETL now correctly handles all Categorial-type columns
  in input DataFrames. The fix also improves execution time of
  transform calls by 2-3x (#20).

[0.1.5] - 2017-10-31

Added

• Added check_null_cols argument to check for null columns (#13)