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@dsherry dsherry released this 24 Nov 22:12
· 1399 commits to main since this release
v0.16.0
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v0.16.0 Nov. 24, 2020

Enhancements

  • Updated pipelines and make_pipeline to accept Woodwork inputs #1393
  • Updated components to accept Woodwork inputs #1423
  • Added ability to freeze hyperparameters for AutoMLSearch #1284
  • Added Target Encoder into transformer components #1401
  • Added callback for error handling in AutoMLSearch #1403
  • Added the index id to the explain_predictions_best_worst output to help users identify which rows in their data are included #1365
  • The top_k features displayed in explain_predictions_* functions are now determined by the magnitude of shap values as opposed to the top_k largest and smallest shap values. #1374
  • Added a problem type for time series regression #1386
  • Added a is_defined_for_problem_type method to ObjectiveBase #1386
  • Added a random_state parameter to make_pipeline_from_components function #1411
  • Added DelayedFeaturesTransformer #1396
  • Added a TimeSeriesRegressionPipeline class #1418
  • Removed core-requirements.txt from the package distribution #1429
  • Updated data check messages to include a "code" and "details" fields #1451 #1462
  • Added a TimeSeriesSplit data splitter for time series problems #1441
  • Added a problem_configuration parameter to AutoMLSearch #1457

Fixes

  • Fixed IndexError raised in AutoMLSearch when ensembling = True but only one pipeline to iterate over #1397
  • Fixed stacked ensemble input bug and LightGBM warning and bug in AutoMLSearch #1388
  • Updated enum classes to show possible enum values as attributes #1391
  • Updated calls to Woodwork's to_pandas() to to_series() and to_dataframe() #1428
  • Fixed bug in OHE where column names were not guaranteed to be unique #1349
  • Fixed bug with percent improvement of ExpVariance objective on data with highly skewed target #1467

Changes

  • Changed OutliersDataCheck to return the list of columns, rather than rows, that contain outliers #1377
  • Simplified and cleaned output for Code Generation #1371
  • Updated data checks to return dictionary of warnings and errors instead of a list #1448
  • Updated AutoMLSearch to pass Woodwork data structures to every pipeline (instead of pandas DataFrames) #1450
  • Update AutoMLSearch to default to max_batches=1 instead of max_iterations=5 #1452

Documentation Changes

  • Added description of CLA to contributing guide, updated description of draft PRs #1402
  • Updated documentation to include all data checks, DataChecks, and usage of data checks in AutoML #1412
  • Updated docstrings from np.array to np.ndarray #1417
  • Added section on stacking ensembles in AutoMLSearch documentation #1425

Testing Changes

  • Removed category_encoders from test-requirements.txt #1373
  • Tweak codecov.io settings again to avoid flakes #1413
  • Modified make lint to check notebook versions in the docs #1431
  • Modified make lint-fix to standardize notebook versions in the docs #1431
  • Use new version of pull request Github Action for dependency check #1443
  • Reduced number of workers for tests to 4 #1447

Breaking Changes

  • The top_k and top_k_features parameters in explain_predictions_* functions now return k features as opposed to 2 * k features #1374
  • Renamed problem_type to problem_types in RegressionObjective, BinaryClassificationObjective, and MulticlassClassificationObjective #1319
  • Data checks now return a dictionary of warnings and errors instead of a list #1448
  • 🦃 🚀
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