Changelog

Future Releases

• Enhancements

• Fixes

• Changes

• Documentation Changes

• Testing Changes

v0.6.0 Dec. 16, 2019

• Enhancements

  • Added ability to create a plot of feature importances #133

  • Add early stopping to AutoML using patience and tolerance parameters #241

  • Added ROC and confusion matrix metrics and plot for classification problems and introduce PipelineSearchPlots class #242

  • Enhanced AutoML results with search order #260

• Fixes

  • Lower botocore requirement #235

  • Fixed decision_function calculation for FraudCost objective #254

  • Fixed return value of Recall metrics #264

• Changes

  • Renamed automl classes to AutoRegressionSearch and AutoClassificationSearch #287

  • Updating demo datasets to retain column names #223

  • Moving pipeline visualization to PipelinePlots class #228

  • Standarizing inputs as pd.Dataframe / pd.Series #130

  • Enforcing that pipelines must have an estimator as last component #277

  • Added ipywidgets as a dependency in requirements.txt #278

• Documentation Changes

  • Adding class properties to API reference #244

  • Fix and filter FutureWarnings from scikit-learn #249, #257

  • Adding Linear Regression to API reference and cleaning up some Sphinx warnings #227

• Testing Changes

  • Added support for testing on Windows with CircleCI #226

  • Added support for doctests #233

Warning

Breaking Changes

• The fit() method for AutoClassifier and AutoRegressor has been renamed to search().

• AutoClassifier has been renamed to AutoClassificationSearch

• AutoRegressor has been renamed to AutoRegressionSearch

• AutoClassificationSearch.results and AutoRegressionSearch.results now is a dictionary with pipeline_results and search_order keys. pipeline_results can be used to access a dictionary that is identical to the old .results dictionary. Whereas,``search_order`` returns a list of the search order in terms of pipeline id.

• Pipelines now require an estimator as the last component in component_list. Slicing pipelines now throws an NotImplementedError to avoid returning Pipelines without an estimator.

v0.5.2 Nov. 18, 2019

• Enhancements

  • Adding basic pipeline structure visualization #211

• Documentation Changes

  • Added notebooks to build process #212

v0.5.1 Nov. 15, 2019

• Enhancements

  • Added basic outlier detection guardrail #151

  • Added basic ID column guardrail #135

  • Added support for unlimited pipelines with a max_time limit #70

  • Updated .readthedocs.yaml to successfully build #188

• Fixes

  • Removed MSLE from default additional objectives #203

  • Fixed random_state passed in pipelines #204

  • Fixed slow down in RFRegressor #206

• Changes

  • Pulled information for describe_pipeline from pipeline’s new describe method #190

  • Refactored pipelines #108

  • Removed guardrails from Auto(*) #202, #208

• Documentation Changes

  • Updated documentation to show max_time enhancements #189

  • Updated release instructions for RTD #193

  • Added notebooks to build process #212

  • Added contributing instructions #213

  • Added new content #222

v0.5.0 Oct. 29, 2019

• Enhancements

  • Added basic one hot encoding #73

  • Use enums for model_type #110

  • Support for splitting regression datasets #112

  • Auto-infer multiclass classification #99

  • Added support for other units in max_time #125

  • Detect highly null columns #121

  • Added additional regression objectives #100

  • Show an interactive iteration vs. score plot when using fit() #134

• Fixes

  • Reordered describe_pipeline #94

  • Added type check for model_type #109

  • Fixed s units when setting string max_time #132

  • Fix objectives not appearing in API documentation #150

• Changes

  • Reorganized tests #93

  • Moved logging to its own module #119

  • Show progress bar history #111

  • Using cloudpickle instead of pickle to allow unloading of custom objectives #113

  • Removed render.py #154

• Documentation Changes

  • Update release instructions #140

  • Include additional_objectives parameter #124

  • Added Changelog #136

• Testing Changes

  • Code coverage #90

  • Added CircleCI tests for other Python versions #104

  • Added doc notebooks as tests #139

  • Test metadata for CircleCI and 2 core parallelism #137

v0.4.1 Sep. 16, 2019

• Enhancements

  • Added AutoML for classification and regressor using Autobase and Skopt #7 #9

  • Implemented standard classification and regression metrics #7

  • Added logistic regression, random forest, and XGBoost pipelines #7

  • Implemented support for custom objectives #15

  • Feature importance for pipelines #18

  • Serialization for pipelines #19

  • Allow fitting on objectives for optimal threshold #27

  • Added detect label leakage #31

  • Implemented callbacks #42

  • Allow for multiclass classification #21

  • Added support for additional objectives #79

• Fixes

  • Fixed feature selection in pipelines #13

  • Made random_seed usage consistent #45

• Documentation Changes

  • Documentation Changes

  • Added docstrings #6

  • Created notebooks for docs #6

  • Initialized readthedocs EvalML #6

  • Added favicon #38

• Testing Changes

  • Added testing for loading data #39

v0.2.0 Aug. 13, 2019

• Enhancements

  • Created fraud detection objective #4

v0.1.0 July. 31, 2019

• First Release

• Enhancements

  • Added lead scoring objecitve #1

  • Added basic classifier #1

• Documentation Changes

  • Initialized Sphinx for docs #1