v0.49.0

Enhancements

• Added use_covariates parameter to ARIMARegressor #3407
• AutoMLSearch will set use_covariates to False for ARIMA when dataset is large #3407
• Add ability to retrieve logical types to a component in the graph via get_component_input_logical_types #3428
• Add ability to get logical types passed to the last component via last_component_input_logical_types #3428

Fixes

• Fix conda build after PR 3407 #3429

Changes

• Moved model understanding metrics from graph.py into a separate file #3417
• Unpin click dependency #3420
• For IterativeAlgorithm, put time series algorithms first #3407
• Use prophet-prebuilt to install prophet in extras #3407

Breaking Changes

• Moved model understanding metrics from graph.py to metrics.py #3417

v0.48.0

v0.48.0 Mar. 28, 2022

Enhancements

• Replaced pipeline_parameters and custom_hyperparameters with search_parameters in AutoMLSearch #3373
• Add support for oversampling in time series classification problems #3387

Fixes

• Fixed TimeSeriesFeaturizer to make it deterministic when creating and choosing columns #3384
• Fixed bug where Email/URL features with missing values would cause the imputer to error out #3388

Changes

• Update maintainers to add Frank #3382
• Allow woodwork version 0.14.0 to be installed #3381
• Moved partial dependence functions from graph.py to a separate file #3404
• Pin click at 8.0.4 due to incompatibility with black #3413

Documentation Changes

• Added automl user guide section covering search algorithms #3394
• Updated broken links and automated broken link detection #3398
• Upgraded nbconvert #3402, #3411

Testing Changes

• Updated scheduled workflows to only run on Alteryx owned repos (#3395)
• Exclude documentation versions other than latest from broken link check #3401

Breaking Changes

• Moved partial dependence functions from graph.py to partial_dependence.py #3404

v0.47.0

v0.47.0 Mar. 17, 2022

Enhancements

• Added TimeSeriesFeaturizer into ARIMA-based pipelines #3313
• Added caching capability for ensemble training during AutoMLSearch #3257
• Added new error code for zero unique values in NoVarianceDataCheck #3372

Fixes

• Fixed get_pipelines to reset pipeline threshold for binary cases #3360

Changes

• Update maintainers #3365

Documentation Changes

• Fixed documentation links to point to correct pages #3358

Testing Changes

• Checkout main branch in build_conda_pkg job #3375

v0.46.0

v0.46.0 Mar. 3, 2022

Enhancements

• Added test_size parameter to ClassImbalanceDataCheck #3341
• Make target optional for NoVarianceDataCheck #3339

Changes

• Removed python_version<3.9 environment marker from sktime dependency #3332
• Updated DatetimeFormatDataCheck to return all messages and not return early if NaNs are detected #3354

Documentation Changes

• Added in-line tabs and copy-paste functionality to documentation, overhauled Install page #3353

v0.45.0

v0.45.0 Feb. 18, 2022

Enhancements

• Added support for pandas >= 1.4.0 #3324
• Standardized feature importance for estimators #3305
• Replaced usage of private method with Woodwork's public get_subset_schema method #3325

Fixes

Changes

• Added an is_cv property to the datasplitters used #3297
• Changed SimpleImputer to ignore Natural Language columns #3324
• Added drop NaN component to some time series pipelines #3310

Documentation Changes

• Update README.md with Alteryx link (#3319)
• Added formatting to the AutoML user guide to shorten result outputs #3328

Testing Changes

• Add auto approve dependency workflow schedule for every 30 mins #3312

v0.44.0

v0.44.0 Feb. 4, 2022

Enhancements

• Updated DefaultAlgorithm to also limit estimator usage for long-running multiclass problems #3099
• Added make_pipeline_from_data_check_output() utility method #3277
• Added more specific data check errors to DatetimeFormatDataCheck #3288

Fixes

• Updated the binary classification pipeline's optimize_thresholds method to use Nelder-Mead #3280
• Fixed bug where feature importance on time series pipelines only showed 0 for time index #3285

Changes

• Removed DateTimeNaNDataCheck and NaturalLanguageNaNDataCheck in favor of NullDataCheck #3260
• Drop support for Python 3.7 #3291
• Updated minimum version of woodwork to v0.12.0 #3290

Documentation Changes

• Update documentation and docstring for validate_holdout_datasets for time series problems #3278
• Fixed mistake in documentation where wrong objective was used for calculating percent-better-than-baseline #3285

Testing Changes

Breaking Changes

• Removed DateTimeNaNDataCheck and NaturalLanguageNaNDataCheck in favor of NullDataCheck #3260
• Dropped support for Python 3.7 #3291

v0.43.0

v0.43.0 Jan. 25, 2022

Enhancements

• Updated new NullDataCheck to return a warning and suggest an action to impute columns with null values #3197
• Updated make_pipeline_from_actions to handle null column imputation #3237
• Updated data check actions API to return options instead of actions and add functionality to suggest and take action on columns with null values #3182

Fixes

• Fixed categorical data leaking into non-categorical sub-pipelines in DefaultAlgorithm #3209
• Fixed Python 3.9 installation for prophet by updating pmdarima version in requirements #3268
• Allowed DateTime columns to pass through PerColumnImputer without breaking #3267

Changes

• Updated DataCheck validate() output to return a dictionary instead of list for actions #3142
• Updated DataCheck validate() API to use the new DataCheckActionOption class instead of DataCheckAction #3152
• Uncapped numba version and removed it from requirements #3263
• Renamed HighlyNullDataCheck to NullDataCheck #3197
• Updated data check validate() output to return a list of warnings and errors instead of a dictionary #3244
• Capped pandas at < 1.4.0 #3274

Testing Changes

• Bumped minimum IPython version to 7.16.3 in test-requirements.txt based on dependabot feedback #3269

Breaking Changes

• Renamed HighlyNullDataCheck to NullDataCheck #3197
• Updated data check validate() output to return a list of warnings and errors instead of a dictionary. See the Data Check or Data Check Actions pages (under User Guide) for examples. #3244
• Removed impute_all and default_impute_strategy parameters from the PerColumnImputer #3267
• Updated PerColumnImputer such that columns not specified in impute_strategies dict will not be imputed anymore #3267

v0.42.0

v0.42.0 Jan. 20, 2022

Enhancements

• Required the separation of training and test data by gap + 1 units to be verified by time_index for time series problems #3208
• Added support for boolean features for ARIMARegressor #3187
• Updated dependency bot workflow to remove outdated description and add new configuration to delete branches automatically #3212
• Added n_obs and n_splits to TimeSeriesParametersDataCheck error details #3246

Fixes

• Fixed classification pipelines to only accept target data with the appropriate number of classes #3185
• Added support for time series in DefaultAlgorithm #3177
• Standardized names of featurization components #3192
• Removed empty cell in text_input.ipynb #3234
• Removed potential prediction explanations failure when pipelines predicted a class with probability 1 #3221
• Dropped NaNs before partial dependence grid generation #3235
• Allowed prediction explanations to be json-serializable #3262
• Fixed bug where InvalidTargetDataCheck would not check time series regression targets #3251
• Fixed bug in are_datasets_separated_by_gap_time_index #3256

Changes

• Raised lowest compatible numpy version to 1.21.0 to address security concerns #3207
• Changed the default objective to MedianAE from R2 for time series regression #3205
• Removed all-nan Unknown to Double logical conversion in infer_feature_types #3196
• Checking the validity of holdout data for time series problems can be performed by calling pipelines.utils.validate_holdout_datasets prior to calling predict #3208

Documentation Changes

Testing Changes

Breaking Changes

• Renamed DateTime Featurizer Component to DateTime Featurizer and Natural Language Featurization Component to Natural Language Featurizer #3192

v0.41.0

v0.41.0 Jan. 10, 2022

Enhancements

• Added string support for DataCheckActionCode #3167
• Added DataCheckActionOption class #3134
• Add issue templates for bugs, feature requests and documentation improvements for GitHub #3199

Fixes

• Fix bug where prediction explanations class_name was shown as float for boolean targets #3179
• Fixed bug in nightly linux tests #3189

Changes

• Removed usage of scikit-learn's LabelEncoder in favor of ours #3161
• Removed nullable types checking from infer_feature_types #3156
• Fixed mean_cv_data and validation_score values in AutoMLSearch.rankings to reflect cv score or NaN when appropriate #3162

Documentation Changes

Testing Changes

• Add workflow to auto-merge dependency PRs if status checks pass #3184

v0.40.0

v0.40.0 Dec. 22, 2021

❄️ ☃️ Happy holidays! ☃️ ❄️

Enhancements

• Added TimeSeriesSplittingDataCheck to DefaultDataChecks to verify adequate class representation in time series classification problems #3141
• Added the ability to accept serialized features and skip computation in DFSTransformer #3106
• Added support for known-in-advance features #3149

Fixes

• Fixed error caused when tuning threshold for time series binary classification #3140

Changes

• TimeSeriesParametersDataCheck was added to DefaultDataChecks for time series problems #3139
• Renamed date_index to time_index in problem_configuration for time series problems #3137
• Updated nlp-primitives minimum version to 2.1.0 #3166
• Updated minimum version of woodwork to v0.11.0 #3171

Documentation Changes

• Added comments to provide clarity on doctests #3155

Testing Changes

• Parameterized tests in test_datasets.py #3145