Release v0.32.1

[chukarsten]

v0.32.1 Sep. 10, 2021

Enhancements

• Added verbose flag to AutoMLSearch to run search in silent mode by default Simplify logging behavior #2645
• Added label encoder to XGBoostClassifier to remove the warning Add label encoder to XGBoost #2701
• Set eval_metric to logloss for XGBoostClassifier Set eval_metric for xgboost #2741
• Added support for woodwork versions 0.7.0 and 0.7.1 Add support for ww 0.7.0 and 0.7.1 #2743
• Changed explain_predictions functions to display original feature values Display original feature values in explain predictions #2759
• Added X_train and y_train to graph_prediction_vs_actual_over_time and get_prediction_vs_actual_over_time_data Pass X_train and y_train to graph_prediction_vs_actual_over_time #2762
• Added forecast_horizon as a required parameter to time series pipelines and AutoMLSearch Add forecast horizon as a required parameter for time series problems #2697
• Added predict_in_sample and predict_proba_in_sample methods to time series pipelines to predict on data where the target is known, e.g. cross-validation Add forecast horizon as a required parameter for time series problems #2697

Fixes

• Fixed bug where _catch_warnings assumed all warnings were PipelineNotUsed Catch only ParameterNotUsed warnings in _catch_warnings #2753
• Fixed bug where Imputer.transform would erase ww typing information prior to handing data to the SimpleImputer Fix Imputer so that it does not erase ww info during transform #2752
• Fixed bug where Oversampler could not be copied Remove imblearn from Oversampler attribute #2755

Changes

• Deleted drop_nan_target_rows utility method Delete drop_nan_target_rows util method #2737
• Removed default logging setup and debugging log file Simplify logging behavior #2645
• Changed the default n_jobs value for XGBoostClassifier and XGBoostRegressor to 12 Change default n_jobs value for XGBoost #2757
• Changed TimeSeriesBaselineEstimator to only work on a time series pipeline with a DelayedFeaturesTransformer Add forecast horizon as a required parameter for time series problems #2697
• Added X_train and y_train as optional parameters to pipeline predict, predict_proba. Only used for time series pipelines Add forecast horizon as a required parameter for time series problems #2697
• Added training_data and training_target as optional parameters to explain_predictions and explain_predictions_best_worst to support time series pipelines Add forecast horizon as a required parameter for time series problems #2697
• Changed time series pipeline predictions to no longer output series/dataframes padded with NaNs. A prediction will be returned for every row in the X input Add forecast horizon as a required parameter for time series problems #2697

Documentation Changes

• Specified installation steps for Prophet Update installation docs for Prophet #2713
• Added documentation for data exploration on data check actions Data exploration on Data Check Actions #2696
• Added a user guide entry for time series modelling Add forecast horizon as a required parameter for time series problems #2697

Testing Changes

• Fixed flaky TargetDistributionDataCheck test for very_lognormal distribution Fixing flaky TargetDistributionDataCheck test #2748

Breaking Changes

• Removed default logging setup and debugging log file Simplify logging behavior #2645
• Added X_train and y_train to graph_prediction_vs_actual_over_time and get_prediction_vs_actual_over_time_data Pass X_train and y_train to graph_prediction_vs_actual_over_time #2762
• Added forecast_horizon as a required parameter to time series pipelines and AutoMLSearch Add forecast horizon as a required parameter for time series problems #2697
• Changed TimeSeriesBaselineEstimator to only work on a time series pipeline with a DelayedFeaturesTransformer Add forecast horizon as a required parameter for time series problems #2697
• Added X_train and y_train as required parameters for predict and predict_proba in time series pipelines Add forecast horizon as a required parameter for time series problems #2697
• Added training_data and training_target as required parameters to explain_predictions and explain_predictions_best_worst for time series pipelines Add forecast horizon as a required parameter for time series problems #2697

[codecov]

Codecov Report

Merging #2769 (aa5c803) into main (bb8329b) will not change coverage.
The diff coverage is 100.0%.

@@          Coverage Diff          @@
##            main   #2769   +/-   ##
=====================================
  Coverage   99.8%   99.8%           
=====================================
  Files        301     301           
  Lines      27889   27889           
=====================================
  Hits       27826   27826           
  Misses        63      63           

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

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[ParthivNaresh]

Solid as a rock