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@dsherry dsherry released this 27 Apr 21:01
v0.9.0
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v0.9.0 Apr. 27, 2020

Enhancements

  • Added accuracy as an standard objective :pr:624
  • Added verbose parameter to load_fraud :pr:560
  • Added Balanced Accuracy metric for binary, multiclass :pr:612 :pr:661
  • Added XGBoost regressor and XGBoost regression pipeline :pr:666
  • Added Accuracy metric for multiclass :pr:672
  • Added objective name in AutoBase.describe_pipeline :pr:686

Fixes

  • Removed direct access to cls.component_graph :pr:595
  • Add testing files to .gitignore :pr:625
  • Remove circular dependencies from Makefile :pr:637
  • Add error case for normalize_confusion_matrix() :pr:640
  • Fixed XGBoostClassifier and XGBoostRegressor bug with feature names that contain [, ], or < :pr:659
  • Update make_pipeline_graph to not accidentally create empty file when testing if path is valid :pr:649
  • Fix pip installation warning about docsutils version, from boto dependency :pr:664
  • Removed zero division warning for F1/precision/recall metrics :pr:671
  • Fixed summary for pipelines without estimators :pr:707

Changes

  • Updated default objective for binary/multiseries classification to log loss :pr:613
  • Created classification and regression pipeline subclasses and removed objective as an attribute of pipeline classes :pr:405
  • Changed the output of score to return one dictionary :pr:429
  • Created binary and multiclass objective subclasses :pr:504
  • Updated objectives API :pr:445
  • Removed call to get_plot_data from AutoML :pr:615
  • Set raise_error to default to True for AutoML classes :pr:638
  • Remove unnecessary "u" prefixes on some unicode strings :pr:641
  • Changed one-hot encoder to return uint8 dtypes instead of ints :pr:653
  • Pipeline _name field changed to custom_name :pr:650
  • Removed graphs.py and moved methods into PipelineBase :pr:657, :pr:665
  • Remove s3fs as a dev dependency :pr:664
  • Changed requirements-parser to be a core dependency :pr:673
  • Replace supported_problem_types field on pipelines with problem_type attribute on base classes :pr:678
  • Changed AutoML to only show best results for a given pipeline template in rankings, added full_rankings property to show all :pr:682
  • Update ModelFamily values: don't list xgboost/catboost as classifiers now that we have regression pipelines for them :pr:677
  • Changed AutoML's describe_pipeline to get problem type from pipeline instead :pr:685
  • Standardize import_or_raise error messages :pr:683
  • Updated argument order of objectives to align with sklearn's :pr:698
  • Renamed pipeline.feature_importance_graph to pipeline.graph_feature_importances :pr:700
  • Moved ROC and confusion matrix methods to evalml.pipelines.plot_utils :pr:704
  • Renamed MultiClassificationObjective to MulticlassClassificationObjective, to align with pipeline naming scheme :pr:715

Documentation Changes

  • Fixed some sphinx warnings :pr:593
  • Fixed docstring for AutoClassificationSearch with correct command :pr:599
  • Limit readthedocs formats to pdf, not htmlzip and epub :pr:594 :pr:600
  • Clean up objectives API documentation :pr:605
  • Fixed function on Exploring search results page :pr:604
  • Update release process doc :pr:567
  • AutoClassificationSearch and AutoRegressionSearch show inherited methods in API reference :pr:651
  • Fixed improperly formatted code in breaking changes for changelog :pr:655
  • Added configuration to treat Sphinx warnings as errors :pr:660
  • Removed separate plotting section for pipelines in API reference :pr:657, :pr:665
  • Have leads example notebook load S3 files using https, so we can delete s3fs dev dependency :pr:664
  • Categorized components in API reference and added descriptions for each category :pr:663
  • Fixed Sphinx warnings about BalancedAccuracy objective :pr:669
  • Updated API reference to include missing components and clean up pipeline docstrings :pr:689
  • Reorganize API ref, and clarify pipeline sub-titles :pr:688
  • Add and update preprocessing utils in API reference :pr:687
  • Added inheritance diagrams to API reference :pr:695
  • Documented which default objective AutoML optimizes for :pr:699
  • Create seperate install page :pr:701
  • Include more utils in API ref, like import_or_raise :pr:704
  • Add more color to pipeline documentation :pr:705

Testing Changes

  • Matched install commands of check_latest_dependencies test and it's GitHub action :pr:578
  • Added Github app to auto assign PR author as assignee :pr:477
  • Removed unneeded conda installation of xgboost in windows checkin tests :pr:618
  • Update graph tests to always use tmpfile dir :pr:649
  • Changelog checkin test workaround for release PRs: If 'future release' section is empty of PR refs, pass check :pr:658

Breaking Changes

  • Pipelines will now no longer take an objective parameter during instantiation, and will no longer have an objective attribute.
  • fit() and predict() now use an optional objective parameter, which is only used in binary classification pipelines to fit for a specific objective.
  • score() will now use a required objectives parameter that is used to determine all the objectives to score on. This differs from the previous behavior, where the pipeline's objective was scored on regardless.
  • score() will now return one dictionary of all objective scores.
  • ROC and ConfusionMatrix plot methods via Auto(*).plot have been removed by :pr:615 and are replaced by roc_curve and confusion_matrix in evamlm.pipelines.plot_utils in :pr:704
  • normalize_confusion_matrix has been moved to evalml.pipelines.plot_utils :pr:704
  • Pipelines _name field changed to custom_name
  • Pipelines supported_problem_types field is removed because it is no longer necessary :pr:678
  • Updated argument order of objectives' objective_function to align with sklearn :pr:698
  • pipeline.feature_importance_graph has been renamed to pipeline.graph_feature_importances in :pr:700
  • Removed unsupported MSLE objective :pr:704
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