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Changelog

Future Releases
  • Enhancements
  • Fixes
  • Changes
  • Documentation Changes
  • Testing Changes
v0.8.0 Apr. 1, 2020
  • Enhancements
    • Add normalization option and information to confusion matrix 484
    • Add util function to drop rows with NaN values 487
    • Renamed PipelineBase.name as PipelineBase.summary and redefined PipelineBase.name as class property 491
    • Added access to parameters in Pipelines with PipelineBase.parameters (used to be return of PipelineBase.describe) 501
    • Added fill_value parameter for SimpleImputer 509
    • Added functionality to override component hyperparemeters and made pipelines take hyperparemeters from components 516
    • Allow numpy.random.RandomState for random_state parameters 556
  • Fixes
  • Changes
    • Undo version cap in XGBoost placed in 402 and allowed all released of XGBoost 407
    • Support pandas 1.0.0 486
    • Made all references to the logger static 503
    • Refactored model_type parameter for components and pipelines to model_family 507
    • Refactored problem_types for pipelines and components into supported_problem_types 515
    • Moved pipelines/utils.save_pipeline and pipelines/utils.load_pipeline to PipelineBase.save and PipelineBase.load 526
    • Limit number of categories encoded by OneHotEncoder 517
  • Documentation Changes
    • Updated API reference to remove PipelinePlot and added moved PipelineBase plotting methods 483
    • Add code style and github issue guides 463 512
    • Updated API reference for to surface class variables for pipelines and components 537
  • Testing Changes
    • Added automated dependency check PR 482, 505
    • Updated automated dependency check comment 497
    • Have build_docs job use python executor, so that env vars are set properly 547
    • Run windows unit tests on PRs 557

Warning

Breaking Changes

  • AutoClassificationSearch and AutoRegressionSearch's model_types parameter has been refactored into allowed_model_families
  • ModelTypes enum has been changed to ModelFamily
  • Components and Pipelines now have a model_family field instead of model_type
  • get_pipelines utility function now accepts model_families as an argument instead of model_types
  • PipelineBase.name no longer returns structure of pipeline and has been replaced by PipelineBase.summary
  • PipelineBase.problem_types and Estimator.problem_types has been renamed to supported_problem_types
  • pipelines/utils.save_pipeline and pipelines/utils.load_pipeline moved to PipelineBase.save and PipelineBase.load
v0.7.0 Mar. 9, 2020
  • Enhancements
    • Added emacs buffers to .gitignore 350
    • Add CatBoost (gradient-boosted trees) classification and regression components and pipelines 247
    • Added Tuner abstract base class 351
    • Added n_jobs as parameter for AutoClassificationSearch and AutoRegressionSearch 403
    • Changed colors of confusion matrix to shades of blue and updated axis order to match scikit-learn's 426
    • Added PipelineBase graph and feature_importance_graph methods, moved from previous location 423
    • Added support for python 3.8 462
  • Fixes
    • Fixed ROC and confusion matrix plots not being calculated if user passed own additional_objectives 276
    • Fixed ReadtheDocs FileNotFoundError exception for fraud dataset 439
  • Changes
    • Added n_estimators as a tunable parameter for XGBoost 307
    • Remove unused parameter ObjectiveBase.fit_needs_proba 320
    • Remove extraneous parameter component_type from all components 361
    • Remove unused rankings.csv file 397
    • Downloaded demo and test datasets so unit tests can run offline 408
    • Remove _needs_fitting attribute from Components 398
    • Changed plot.feature_importance to show only non-zero feature importances by default, added optional parameter to show all 413
    • Refactored PipelineBase to take in parameter dictionary and moved pipeline metadata to class attribute 421
    • Dropped support for Python 3.5 438
    • Removed unused apply.py file 449
    • Clean up requirements.txt to remove unused deps 451
    • Support installation without all required dependencies 459
  • Documentation Changes
    • Update release.md with instructions to release to internal license key 354
  • Testing Changes
    • Added tests for utils (and moved current utils to gen_utils) 297
    • Moved XGBoost install into it's own separate step on Windows using Conda 313
    • Rewind pandas version to before 1.0.0, to diagnose test failures for that version 325
    • Added dependency update checkin test 324
    • Rewind XGBoost version to before 1.0.0 to diagnose test failures for that version 402
    • Update dependency check to use a whitelist 417
    • Update unit test jobs to not install dev deps 455

Warning

Breaking Changes

  • Python 3.5 will not be actively supported.
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
    • Components return self on fit 289
  • 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
    • Added Random and Grid Search Tuners 240
  • 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