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0.4.1 (2021-09-06)

Fixes:

  • Add missing dependency on packaging (#247). Thank you @sim-san for reporting and fixing!
  • Fixed an issue causing routed parameters (fit__class_weight) to be overridden by non-routed parameters, including default values (class_weight=None) (#244). Thank you @8549 for reporting the issue.
  • Fix handling of class_weight="balanced" (#245)

0.4.0 (2021-08-30)

Features:

  • Support routed parameters to callbacks (#233)

Changes:

  • Official support for extra keyword arguments (**kwargs) in fit(), predict() and predict_proba() that are routed directly to Keras (#238)
  • Remove hard dependency on tensorflow, allowing users to choose tensorflow-cpu or other distributions in environments where they can't control pip arguments (#237)
  • Remove hard dependency on tensorflow, allowing users to choose tensorflow-cpu or other distributions (#237)

0.3.1 (2021-04-12)

Fixes:

  • Fixes a bug in inverse-transforms of predictions for multiclass labels that are not one-hot encoded (#229). Credit to RKCZ on StackOverflow #67019157 for reporting the issue.

0.3.0 (2021-04-07)

Thank you to all of the collaborators that found bugs and submitted PRs to SciKeras!

v0.3.0 is a minor release that consists mainly of bug fixes, although we have made huge improvements under the hood as well.

Features:

  • Implement batch_size=-1 (#194)
  • Lots of documentation improvements (#200, #197, #178, #176, #174)

Fixes:

  • Fix a bug in meta parameter collection (#171)
  • Allow epochs to be passed as a keyword argument to fit (#154)
  • Fix the signature of BaseWrapper.scorer (#169)
  • Fix inverse transforms for one-hot encoded targets (#189)

Contributors to this release:

  • @stsievert
  • @data-hound

0.2.1 (2020-12-06)

Thank you to @stsievert for your continued support and contributions!

Release notes:

  • Support autoencoders and more general use cases via BaseWrapper (#123)
  • Fix slowdown caused by sample_weight processing (reported in DaskML#764, fixed in #123)
  • Documentation improvements (#134, #135, #145 and #138)
  • Fix the initialize method in KerasClassifier (#140)

0.2.0 (2020-10-03)

  • Move data transformations to a Scikit-Learn Transformer based interface (#88)
  • Add Keras parameters to BaseWrapper.init (loss, optimizer, etc) (#47, #55)
  • Remove needless checks/array creation (#63, #59)
  • Make pre/post processing functions public (#42)
  • Some stability around BaseWrapper.__call__ (#35)
  • Cleanup around loss names (#38, #35)
  • Parameter routing (#67)
  • Rename build_fn to model with deprecation cycle (#98)
  • Add ability for SciKeras to compile models (#66)
  • class_weights parameter (#52, #103)
  • classes param for partial_fit (#69, #104)
  • Provide an epochs parameter (#51, #114)
  • Updated docs, now hosted on RTD (#58, #73)
  • Checks to make sure models are correctly compiled (#86, #100, #88)

0.1.8 (2020-06-30)

  • Add support for partial fitting and warm starts (#17, thank you @stsievert!).
  • Add support for random states via the random_state parameter (#27).
  • Scikit-Learn SLEP10 compliance (#26).
  • Fix unnecessary data reshaping warnings (#23).

0.1.7 (2020-05-18)

  • Versioning fix.

0.1.6 (2020-05-18)

  • Rename repo.
  • Derive BaseWrapper from BaseEstimator.
  • Python 3.8 support.

0.1.5.post1 (2020-05-13)

  • Deprecate Python 3.5 (#11).
  • Fix prebuilt model bug (#5).
  • Clean up serialization (#7).
  • Implement scikit-learn estimator tests (#10).

0.1.4 (2020-04-12)

  • Offload output type detection for classification to sklearn.utils.multiclass.type_of_target.
  • Add documentation.
  • Some file cleanup.

0.1.3 (2020-04-11)

  • First release on PyPI.