Release v0.16.0

[dsherry]

v0.16.0 Nov. 24, 2020

Enhancements

• Updated pipelines and make_pipeline to accept Woodwork inputs Update pipelines and make_pipelines to accept Woodwork DataTables #1393
• Updated components to accept Woodwork inputs Update components to accept Woodwork inputs #1423
• Added ability to freeze hyperparameters for AutoMLSearch Freeze Hyperparameters for AutoMLSearch #1284
• Added Target Encoder into transformer components Add Target Encoder to Components #1401
• Added callback for error handling in AutoMLSearch Add 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 Adding the Index ID to explain_prediction_best_worst_output #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. Displaying the top_k features with largest shap value magnitudes #1374
• Added a problem type for time series regression Add TimeSeriesRegression problem type #1386
• Added a is_defined_for_problem_type method to ObjectiveBase Add TimeSeriesRegression problem type #1386
• Added a random_state parameter to make_pipeline_from_components function make_pipeline_from_components accepts a random state #1411
• Added DelayedFeaturesTransformer Add a DelayedFeaturesTransformer #1396
• Added a TimeSeriesRegressionPipeline class Timeseries regression pipeline #1418
• Removed core-requirements.txt from the package distribution Removing core-requirements from installed package #1429
• Updated data check messages to include a "code" and "details" fields Update data check message to include a "code" and "details" fields #1451 Fix high variance cv message for automl #1462
• Added a TimeSeriesSplit data splitter for time series problems Data split for time series #1441
• Added a problem_configuration parameter to AutoMLSearch Add problem_configuration parameter to AutoMLSearch #1457

Fixes

• Fixed IndexError raised in AutoMLSearch when ensembling = True but only one pipeline to iterate over Fixed IndexError when ensembling = True but number of pipelines to search over is 1 #1397
• Fixed stacked ensemble input bug and LightGBM warning and bug in AutoMLSearch Fix stacked ensemble and LightGBM errors in AutoMLSearch #1388
• Updated enum classes to show possible enum values as attributes Fix documentation for enums #1391
• Updated calls to Woodwork's to_pandas() to to_series() and to_dataframe() Update Woodwork to_pandas to to_dataframe and to_series #1428
• Fixed bug in OHE where column names were not guaranteed to be unique Modifying ohe get_feature_names so encoded columns are always unique #1349
• Fixed bug with percent improvement of ExpVariance objective on data with highly skewed target When baseline score is close to 0, set percent improved to nan #1467

Changes

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

Documentation Changes

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

Testing Changes

• Removed category_encoders from test-requirements.txt Removing category_encoders from test-requirements.txt #1373
• Tweak codecov.io settings again to avoid flakes Try rounding codecov down instead of up #1413
• Modified make lint to check notebook versions in the docs Adding a script to standardize the notebook versions. #1431
• Modified make lint-fix to standardize notebook versions in the docs Adding a script to standardize the notebook versions. #1431
• Use new version of pull request Github Action for dependency check Update dependency check with new version #1443
• Reduced number of workers for tests to 4 Reduce number of CircleCI workers 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 Displaying the top_k features with largest shap value magnitudes #1374
• Renamed problem_type to problem_types in RegressionObjective, BinaryClassificationObjective, and MulticlassClassificationObjective Rename LabelLeakageDataCheck to TargetLeakageDataCheck. #1319
• Data checks now return a dictionary of warnings and errors instead of a list Update data checks to return a dictionary #1448
• 🦃 🚀

[codecov]

Codecov Report

Merging #1468 (3ef8c43) into main (a56ef73) will not change coverage.
The diff coverage is 100.0%.

@@           Coverage Diff           @@
##             main    #1468   +/-   ##
=======================================
  Coverage   100.0%   100.0%           
=======================================
  Files         223      223           
  Lines       15019    15019           
=======================================
  Hits        15012    15012           
  Misses          7        7           

Impacted Files	Coverage Δ
evalml/__init__.py	100.0% <100.0%> (ø)

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[bchen1116]

🦃🚀

[freddyaboulton]

Awesome!

[dsherry]

Perf test results here.