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