sktime

Maintenance release with scheduled deprecations and change actions.

For the last non-maintenance content update, see 0.34.1.

Dependency changes

scikit-base bounds have been updated to >=0.6.1,<0.13.0

skpro (probability distributions soft dependency) bounds have been updated to >=2,<2.9.0

Deprecations and removals

From sktime 0.38.0 , forecasters’ predict_proba will require skpro to be present in the python environment, for distribution objects to represent distributional forecasts. Since sktime 0.35.0 , an error is raised upon call of forecaster predict_proba if skpro is not present in the environment. Users of forecasters’ predict_proba should ensure that skpro is installed in the environment.

The probability distributions module sktime.proba deprecated and will be fully replaced by skpro in sktime 0.38.0 . Until sktime 0.38.0 , imports from sktime.proba will continue working, defaulting to sktime.proba if skpro is not present, otherwise redirecting imports to skpro objects. Since sktime 0.35.0 , an error is raised if skpro is not present in the environment, otherwise imports are redirected to skpro . Direct or indirect users of sktime.proba should ensure skpro is installed in the environment. Direct users of the sktime.proba module should, in addition, replace any imports from sktime.proba with imports from skpro.distributions .

in neuralforecast facing estimator interfaces, the default for the broadcasting parameter has been consistently changed to False .

Maintenance

[MNT] Dependabot: Update scikit-base requirement from <0.12.0,>=0.6.1 to >=0.6.1,<0.13.0 ( #7392 ) @dependabot[bot]

[MNT] Dependabot: Update skpro requirement from <2.8.0,>=2 to >=2,<2.9.0 ( #7406 ) @dependabot[bot]

[MNT] bound peft<0.14.0 ( #7495 ) @fkiraly

[MNT] 0.35.0 deprecations and change actions ( #7485 ) @fkiraly

[MNT] remove top level import of transformers ( #7491 ) @yarnabrina

[MNT] add upper bound to skforecast autoreg adapter ( #7488 ) @yarnabrina

[DOC] fix failing cells in detection notebook after skchange update ( #7483 ) @fkiraly

[BUG] Fix codec error on traditional Chinese Windows systems ( #7498 ) @fnhirwa

Contributors

@fkiraly , @fnhirwa , @yarnabrina

Maintenance release with scheduled deprecations and change actions.

For the last non-maintenance content update, see 0.34.1.

Dependency changes

• scikit-base bounds have been updated to >=0.6.1,<0.13.0

• skpro (probability distributions soft dependency) bounds have been updated to >=2,<2.9.0

Deprecations and removals

• From sktime 0.38.0, forecasters' predict_proba will require skpro to be present in the python environment, for distribution objects to represent distributional forecasts. Since sktime 0.35.0, an error is raised upon call of forecaster predict_proba if skpro is not present in the environment. Users of forecasters' predict_proba should ensure that skpro is installed in the environment.

• The probability distributions module sktime.proba deprecated and will be fully replaced by skpro in sktime 0.38.0. Until sktime 0.38.0, imports from sktime.proba will continue working, defaulting to sktime.proba if skpro is not present, otherwise redirecting imports to skpro objects. Since sktime 0.35.0, an error is raised if skpro is not present in the environment, otherwise imports are redirected to skpro. Direct or indirect users of sktime.proba should ensure skpro is installed in the environment. Direct users of the sktime.proba module should, in addition, replace any imports from sktime.proba with imports from skpro.distributions.

• in neuralforecast facing estimator interfaces, the default for the broadcasting parameter has been consistently changed to False.

Maintenance

• [MNT] [Dependabot](deps): Update scikit-base requirement from <0.12.0,>=0.6.1 to >=0.6.1,<0.13.0 (7392) dependabot[bot]

• [MNT] [Dependabot](deps): Update skpro requirement from <2.8.0,>=2 to >=2,<2.9.0 (7406) dependabot[bot]

• [MNT] bound peft<0.14.0 (7495) fkiraly

• [MNT] 0.35.0 deprecations and change actions (7485) fkiraly

• [MNT] remove top level import of transformers (7491) yarnabrina

• [MNT] add upper bound to skforecast autoreg adapter (7488) yarnabrina

• [DOC] fix failing cells in detection notebook after skchange update (7483) fkiraly

• [BUG] Fix codec error on traditional Chinese Windows systems (7498) fnhirwa

Contributors

fkiraly, fnhirwa, yarnabrina

Highlights

Full rework of detectors API, module is now maturing. @tveten , @alex-jg3 , @fkiraly , @alyssadsouza , @ShivamJ07 , @RobotPsychologist

in forecasting metrics, allow a callable to be passed as sample_weight for dynamic weight generation ( #7288 ) @MarkusSagen

Interfaces to new neuralforecast estimators ( #7434 ) @yarnabrina

Box-Cox bias adjustment for forecasters ( #7268 ) @sanskarmodi8 , @talat-khattatov

SCINet forecaster ( #7400 ) @Sohaib-Ahmed21

Spatio-Temporal DBSCAN clusterer ( #7353 ) @vagechirkov , @vectornd

Signature moments transformer ( #7320 ) @VectorNd

Dependency changes

dask (data container and parallelization back-end soft dependency) bounds have been updated to <2024.11.3

Core interface changes

Forecasting

Forecasting metrics now allow a callable to be passed as sample_weight for dynamic weight generation. The precise contract the callables need to satisfy is documented in the docstrings.

Time series anomalies, changepoints, segmentation

The core API for time series detectors has changed, and has been homogenized with the API of skchange .

The changes are in parts breaking, and require adjustments in the user code. The changes were necessary to ensure a consistent API for time series detectors.

BaseDetector.predict now returns a pd.DataFrame . This DataFrame always has a RangeIndex , with individual rows corresponding to individual events. The DataFrame has at least a column "ilocs" , which contains the integer indices of the detected events, in reference to the argument X passed to predict . The format, for an entry, can be a single integer or a left-closed pd.Interval of integers, indicating either a single point or a segment of points.

an additional column "labels" may be present in cases of labelled events.

BaseDetector.predict_points and predict_segments now also return pd.DataFrame , following the same format as predict , with the difference that predict_points coerces detected events to points, taking start and end points of segments as separate points. predict_segments coerces detected events to segments, possibly single-index segments.

BaseDetector.transform now always returns a pd.DataFrame with, which has at least a column "transform" containing the transformed series.

Enhancements

BaseObject and base framework

[ENH] refactor _check_estimator_types to use record class interface ( #7395 ) @fkiraly

[ENH] parity of _HeterogenousMetaEstimator._check_estimator with skbase and fixes in EnsembleForecaster.init ( #7429 ) @fkiraly

Benchmarking, Metrics, Splitters

[ENH] MSRE-percent forecasting metric ( #7394 ) @jusssch , @fkiraly

Forecasting

[ENH] add RecursiveReductionForecaster to module exports, tests, and documentation ( #4806 ) @fkiraly

[ENH] EnsembleForecaster option to specify multiple copies of same forecaster easily ( #7424 ) @ericjb

[ENH] Add new arguments to neuralforecast rnn and lstm ( #7422 ) @yarnabrina

[ENH] Box-Cox bias adjustment for forecasters ( #7268 ) @sanskarmodi8 , @talat-khattatov

[ENH] in forecasting metrics, allow a callable to be passed as sample_weight for dynamic weight generation ( #7288 ) @MarkusSagen

[ENH] SCINet forecaster ( #7400 ) @Sohaib-Ahmed21

[ENH] Reduce memory footprint of statsmodels adapter - save necessary _y info to remove need for _y ( #7417 ) @hudsonhoch

[ENH] Interface new neuralforecast estimators ( #7434 ) @yarnabrina

Time series anomalies, changepoints, segmentation

[ENH] Test parameter set for STRAY ( #7420 ) @tajir0

[ENH] add _transform_score template and remove dead fmt related code from detectors ( #7425 ) @ShivamJ07

[ENH] homogenization of sktime and skchange detection API - base class predict return type ( #7433 ) @alyssadsouza

[ENH] rename private make_annotation_problem to make_detection_problem ( #7436 ) @fkiraly

[ENH] minor improvements to BaseDetector ( #7435 ) @fkiraly

[ENH] move detector non-suite tests to detection folder ( #7445 ) @fkiraly

[ENH] homogenization of sktime and skchange detection API - part 1 - base class and y argument ( #7342 ) @fkiraly

[ENH] homogenization of sktime and skchange detection API - part 2 - base class transform return type ( #7432 ) @alyssadsouza

[ENH] move detector classes to detection module ( #7448 ) @fkiraly

[ENH] conditional testing and imports for estimator specific tests in detection module ( #7446 ) @fkiraly

[ENH] add detector specific tags to the tag registry and tags API reference ( #7443 ) @liya-zhu

[ENH] detector dummies ( #7440 ) @fkiraly

[ENH] Changed scitype name "series-annotator" to "detector" ( #7361 ) @jgyfutub

[ENH] homogenization of sktime and skchange detection API - base class predict_scores return type ( #7460 ) @alyssadsouza

[ENH] homogenization of sktime and skchange detection API - base class predict_points return type ( #7459 ) @alyssadsouza

[ENH] skchange rename of Capa to CAPA ( #7457 ) @fkiraly

[ENH] move detector tests to detection module ( #7455 , #7464 ) @fkiraly

[ENH] renaming of detector suite tests ( #7465 ) @fkiraly

[ENH] fix API incompatibility of SubLOF detector ( #7468 ) @fkiraly

[ENH] add skchange change point detectors as placeholder records ( #7458 ) @ShivamJ07 , @fkiraly

[ENH] add placeholder records for skchange segment anomaly detectors ( #7470 ) @fkiraly

[ENH] update DetectorPipeline and DetectorAsTransformer inner calls and docstrings ( #7475 ) @fkiraly

[ENH] homogenization of sktime and skchange detection API - predict , predict_points , predict_segments ( #7476 ) @fkiraly

Time series classification

[ENH] second test parameter to Arsenal classifier ( #7335 ) @jusssch

Time series clustering

[ENH] Spatio-Temporal DBSCAN clusterer ( #7353 ) @vagechirkov , @vectornd

Time series regression

[ENH] Test parameter sets for ComposableTimeSeriesForestRegressor ( #7431 ) @Dehelaan

Transformations

[ENH] Signature Moments transformer ( #7320 ) @VectorNd

[ENH] added test parameter set for ColumnTransformer ( #7442 ) @sanskarmodi8

[ENH] second test parameter set in _multirocket_multivariate ( #7344 ) @medha-14

Test framework

[ENH] detection module suite tests coverage extension for methods ( #6958 ) @Alex-JG3

Documentation

[DOC] fix typos in changelog, better explanation of scoring parameters ( #7324 ) @fkiraly

[DOC] in docstring, rename Example to Examples sections ( #7341 ) @fkiraly

[DOC] add docstring example for DropNA ( #7327 ) @SSROCKS30

[DOC] Fixed sktime logo positioning in the README ( #7322 ) @Akhsuna07

[DOC] Add uni2ts in libs/README.md ( #7348 ) @pranavvp16

[DOC] Small typo on explanation of regression ( #7366 ) @manolotis

[DOC] Add Binary Segmentation Estimator to API reference ( #7379 ) @Dehelaan

[DOC] Add timesfm in libs/README.md ( #7358 ) @geetu040

[DOC] categories for clustering algorithms in API reference ( #7369 ) @fkiraly

[DOC] API reference for data representations ( #7231 ) @fkiraly

[DOC] Improving the installation instructions to improve clarity ( #7339 ) @julian-fong

[DOC] fixes to the mtype API reference ( #7393 ) @fkiraly

[DOC] fix duplications of the word “correspond” ( #7403 ) @fkiraly

[DOC] Add import location to HolidayFeatures docs ( #7401 ) @mjste

[DOC] add rubric for time series detectors to estimator overview ( #7389 ) @gavinkatz001

[DOC] provide proper mathematical description in docstring of sliding window splitter. ( #7376 ) @keitaVigano

[DOC] add detector tags to estimator overview, fix API reference ( #7473 ) @fkiraly

[DOC] improve formatting of forecasting metrics ( #7474 ) @fkiraly

Maintenance

[MNT] allow optuna<4.2 and test 3.13 support ( #7384 ) @fkiraly

[MNT] detection module - move CI from annotation module ( #7456 ) @fkiraly

[MNT] updating versions of pre-commit hooks ( #7461 ) @yarnabrina

[MNT] Dependabot: Update dask requirement from <2024.8.1 to <2024.11.3 ( #7387 ) @dependabot[bot]

[MNT] Dependabot: Update pytest-randomly requirement from <3.16,>=3.15 to >=3.15,<3.17 ( #7338 ) @dependabot[bot]

Fixes

Forecasting

[BUG] rectify ignores-exogeneous-X tag value in Croston ( #7404 ) @yarnabrina

Time series anomalies, changepoints, segmentation

[BUG] fix BaseDetector methods for case of no points detected ( #7439 ) @fkiraly

[BUG] ensure BaseDetector.transform uses iloc indexing ( #7444 ) @fkiraly

[BUG] fix BaseDetector.change_points_to_segments ( #7452 ) @fkiraly

Time series classification

[BUG] fix input shape in CNTCClassifier and CNTCRegressor ( #7269 ) @sanskarmodi8

Time series clustering

[BUG] fix input shape in CNTCClassifier ( #7269 ) @sanskarmodi8

Time series regression

[BUG] fix input shape in CNTCRegressor ( #7269 ) @sanskarmodi8

Test framework

[BUG] fix check_estimator test in case of failure ( #7430 ) @fkiraly

Contributors

@Akhsuna07 , @Alex-JG3 , @alyssadsouza , @Dehelaan , @ericjb , @fkiraly , @gavinkatz001 , @geetu040 , @hudsonhoch , @jgyfutub , @julian-fong , @jusssch , @keitaVigano , @liya-zhu , @manolotis , @MarkusSagen , @medha-14 , @mjste , @pranavvp16 , @sanskarmodi8 , @ShivamJ07 , @Sohaib-Ahmed21 , @SSROCKS30 , @tajir0 , @talat-khattatov , @vagechirkov , @VectorNd , @yarnabrina

Highlights

• Full rework of detectors API, module is now maturing. tveten, alex-jg3, fkiraly, alyssadsouza, ShivamJ07, RobotPsychologist

• in forecasting metrics, allow a callable to be passed as sample_weight for dynamic weight generation (7288) MarkusSagen

• Interfaces to new neuralforecast estimators (7434) yarnabrina

• Box-Cox bias adjustment for forecasters (7268) sanskarmodi8, talat-khattatov

• SCINet forecaster (7400) Sohaib-Ahmed21

• Spatio-Temporal DBSCAN clusterer (7353) vagechirkov, vectornd

• Signature moments transformer (7320) VectorNd

Dependency changes

• dask (data container and parallelization back-end soft dependency) bounds have been updated to <2024.11.3

Core interface changes

Forecasting

Forecasting metrics now allow a callable to be passed as sample_weight for dynamic weight generation. The precise contract the callables need to satisfy is documented in the docstrings.

Time series anomalies, changepoints, segmentation

The core API for time series detectors has changed, and has been homogenized with the API of skchange.

The changes are in parts breaking, and require adjustments in the user code. The changes were necessary to ensure a consistent API for time series detectors.

• BaseDetector.predict now returns a pd.DataFrame. This DataFrame always has a RangeIndex, with individual rows corresponding to individual events. The DataFrame has at least a column "ilocs", which contains the integer indices of the detected events, in reference to the argument X passed to predict. The format, for an entry, can be a single integer or a left-closed pd.Interval of integers, indicating either a single point or a segment of points.

• an additional column "labels" may be present in cases of labelled events.

• BaseDetector.predict_points and predict_segments now also return pd.DataFrame, following the same format as predict, with the difference that predict_points coerces detected events to points, taking start and end points of segments as separate points. predict_segments coerces detected events to segments, possibly single-index segments.

• BaseDetector.transform now always returns a pd.DataFrame with, which has at least a column "transform" containing the transformed series.

Enhancements

BaseObject and base framework

• [ENH] refactor _check_estimator_types to use record class interface (7395) fkiraly

• [ENH] parity of _HeterogenousMetaEstimator._check_estimator with skbase and fixes in EnsembleForecaster.__init__ (7429) fkiraly

Benchmarking, Metrics, Splitters

• [ENH] MSRE-percent forecasting metric (7394) jusssch, fkiraly

Forecasting

• [ENH] add RecursiveReductionForecaster to module exports, tests, and documentation (4806) fkiraly

• [ENH] EnsembleForecaster option to specify multiple copies of same forecaster easily (7424) ericjb

• [ENH] Add new arguments to neuralforecast rnn and lstm (7422) yarnabrina

• [ENH] Box-Cox bias adjustment for forecasters (7268) sanskarmodi8, talat-khattatov

• [ENH] in forecasting metrics, allow a callable to be passed as sample_weight for dynamic weight generation (7288) MarkusSagen

• [ENH] SCINet forecaster (7400) Sohaib-Ahmed21

• [ENH] Reduce memory footprint of statsmodels adapter - save necessary _y info to remove need for _y (7417) hudsonhoch

• [ENH] Interface new neuralforecast estimators (7434) yarnabrina

Time series anomalies, changepoints, segmentation

• [ENH] Test parameter set for STRAY (7420) tajir0

• [ENH] add _transform_score template and remove dead fmt related code from detectors (7425) ShivamJ07

• [ENH] homogenization of sktime and skchange detection API - base class predict return type (7433) alyssadsouza

• [ENH] rename private make_annotation_problem to make_detection_problem (7436) fkiraly

• [ENH] minor improvements to BaseDetector (7435) fkiraly

• [ENH] move detector non-suite tests to detection folder (7445) fkiraly

• [ENH] homogenization of sktime and skchange detection API - part 1 - base class and y argument (7342) fkiraly

• [ENH] homogenization of sktime and skchange detection API - part 2 - base class transform return type (7432) alyssadsouza

• [ENH] move detector classes to detection module (7448) fkiraly

• [ENH] conditional testing and imports for estimator specific tests in detection module (7446) fkiraly

• [ENH] add detector specific tags to the tag registry and tags API reference (7443) liya-zhu

• [ENH] detector dummies (7440) fkiraly

• [ENH] Changed scitype name "series-annotator" to "detector" (7361) jgyfutub

• [ENH] homogenization of sktime and skchange detection API - base class predict_scores return type (7460) alyssadsouza

• [ENH] homogenization of sktime and skchange detection API - base class predict_points return type (7459) alyssadsouza

• [ENH] skchange rename of Capa to CAPA (7457) fkiraly

• [ENH] move detector tests to detection module (7455, 7464) fkiraly

• [ENH] renaming of detector suite tests (7465) fkiraly

• [ENH] fix API incompatibility of SubLOF detector (7468) fkiraly

• [ENH] add skchange change point detectors as placeholder records (7458) ShivamJ07, fkiraly

• [ENH] add placeholder records for skchange segment anomaly detectors (7470) fkiraly

• [ENH] update DetectorPipeline and DetectorAsTransformer inner calls and docstrings (7475) fkiraly

• [ENH] homogenization of sktime and skchange detection API - predict, predict_points, predict_segments (7476) fkiraly

Time series classification

• [ENH] second test parameter to Arsenal classifier (7335) jusssch

Time series clustering

• [ENH] Spatio-Temporal DBSCAN clusterer (7353) vagechirkov, vectornd

Time series regression

• [ENH] Test parameter sets for ComposableTimeSeriesForestRegressor (7431) Dehelaan

Transformations

• [ENH] Signature Moments transformer (7320) VectorNd

• [ENH] added test parameter set for ColumnTransformer (7442) sanskarmodi8

• [ENH] second test parameter set in _multirocket_multivariate (7344) medha-14

Test framework

• [ENH] detection module suite tests coverage extension for methods (6958) Alex-JG3

Documentation

• [DOC] fix typos in changelog, better explanation of scoring parameters (7324) fkiraly

• [DOC] in docstring, rename Example to Examples sections (7341) fkiraly

• [DOC] add docstring example for DropNA (7327) SSROCKS30

• [DOC] Fixed sktime logo positioning in the README (7322) Akhsuna07

• [DOC] Add uni2ts in libs/README.md (7348) pranavvp16

• [DOC] Small typo on explanation of regression (7366) manolotis

• [DOC] Add Binary Segmentation Estimator to API reference (7379) Dehelaan

• [DOC] Add timesfm in libs/README.md (7358) geetu040

• [DOC] categories for clustering algorithms in API reference (7369) fkiraly

• [DOC] API reference for data representations (7231) fkiraly

• [DOC] Improving the installation instructions to improve clarity (7339) julian-fong

• [DOC] fixes to the mtype API reference (7393) fkiraly

• [DOC] fix duplications of the word "correspond" (7403) fkiraly

• [DOC] Add import location to HolidayFeatures docs (7401) mjste

• [DOC] add rubric for time series detectors to estimator overview (7389) gavinkatz001

• [DOC] provide proper mathematical description in docstring of sliding window splitter. (7376) keitaVigano

• [DOC] add detector tags to estimator overview, fix API reference (7473) fkiraly

• [DOC] improve formatting of forecasting metrics (7474) fkiraly

Maintenance

• [MNT] allow optuna<4.2 and test 3.13 support (7384) fkiraly

• [MNT] detection module - move CI from annotation module (7456) fkiraly

• [MNT] updating versions of pre-commit hooks (7461) yarnabrina

• [MNT] [Dependabot](deps): Update dask requirement from <2024.8.1 to <2024.11.3 (7387) dependabot[bot]

• [MNT] [Dependabot](deps): Update pytest-randomly requirement from <3.16,>=3.15 to >=3.15,<3.17 (7338) dependabot[bot]

Fixes

Forecasting

• [BUG] rectify ignores-exogeneous-X tag value in Croston (7404) yarnabrina

Time series anomalies, changepoints, segmentation

• [BUG] fix BaseDetector methods for case of no points detected (7439) fkiraly

• [BUG] ensure BaseDetector.transform uses iloc indexing (7444) fkiraly

• [BUG] fix BaseDetector.change_points_to_segments (7452) fkiraly

Time series classification

• [BUG] fix input shape in CNTCClassifier and CNTCRegressor (7269) sanskarmodi8

Time series clustering

• [BUG] fix input shape in CNTCClassifier (7269) sanskarmodi8

Time series regression

• [BUG] fix input shape in CNTCRegressor (7269) sanskarmodi8

Test framework

• [BUG] fix check_estimator test in case of failure (7430) fkiraly

Contributors

Akhsuna07, Alex-JG3, alyssadsouza, Dehelaan, ericjb, fkiraly, gavinkatz001, geetu040, hudsonhoch, jgyfutub, julian-fong, jusssch, keitaVigano, liya-zhu, manolotis, MarkusSagen, medha-14, mjste, pranavvp16, sanskarmodi8, ShivamJ07, Sohaib-Ahmed21, SSROCKS30, tajir0, talat-khattatov, vagechirkov, VectorNd, yarnabrina

Maintenance release:

full support for python 3.13

scheduled deprecations and change actions.

For last non-maintenance content updates, see 0.33.2.

Dependency changes

numpy bounds have been updated to >=1.21,<2.2

scikit-base bounds have been updated to >=0.6.1,<0.12.0

holidays (transformations soft dependency) bounds have been updated to >=0.29,<0.59

Deprecations and removals

The annotation module will be renamed to detection , starting with 0.34.0. Until a future release not earlier than 0.37.0 or 1.0.0, the module will be available under both names to ensure downwards compatibility of imports.

The annotation soft dependency set will be renamed to detection . The annotation soft dependency set will be available until a future release not earlier than 0.37.0 or 1.0.0, to ensure downwards compatibility of imports.

Maintenance

[MNT] python 3.13 support in pyproject.toml and CI ( #7198 ) @fkiraly

[MNT] disable numpy<2 bound for prophet ( #6740 ) @fkiraly

[MNT] 0.34.0 deprecations and change actions ( #7302 ) @fkiraly

[MNT] prepare rename annotation module to detection - mapped imports ( #7294 ) @fkiraly

[MNT] deduplicate sktime and skbase BaseEstimator ( #7213 ) @fkiraly

[MNT] Dependabot: Update numpy requirement from <2.1,>=1.21 to >=1.21,<2.2 ( #7103 ) @dependabot[bot]

[MNT] Dependabot: Update scikit-base requirement from <0.9.0,>=0.6.1 to >=0.6.1,<0.12.0 ( #7238 ) @dependabot[bot]

[MNT] Dependabot: Update holidays requirement from <0.55,>=0.29 to >=0.29,<0.59 ( #7308 ) @dependabot[bot]

[MNT] Dependabot: Update sphinx-issues requirement from <5.0.0 to <6.0.0 ( #7307 ) @dependabot[bot]

Documentation

[DOC] replace documentation references to “annotation” with “detection” ( #7299 ) @fkiraly

[DOC] change imports in detection tutorial to detection module ( #7306 ) @fkiraly

Maintenance release:

• full support for python 3.13

• scheduled deprecations and change actions.

For last non-maintenance content updates, see 0.33.2.

Dependency changes

• numpy bounds have been updated to >=1.21,<2.2

• scikit-base bounds have been updated to >=0.6.1,<0.12.0

• holidays (transformations soft dependency) bounds have been updated to >=0.29,<0.59

Deprecations and removals

• The annotation module will be renamed to detection, starting with 0.34.0. Until a future release not earlier than 0.37.0 or 1.0.0, the module will be available under both names to ensure downwards compatibility of imports.

• The annotation soft dependency set will be renamed to detection. The annotation soft dependency set will be available until a future release not earlier than 0.37.0 or 1.0.0, to ensure downwards compatibility of imports.

Maintenance

• [MNT] python 3.13 support in pyproject.toml and CI (7198) fkiraly

• [MNT] disable numpy<2 bound for prophet (6740) fkiraly

• [MNT] 0.34.0 deprecations and change actions (7302) fkiraly

• [MNT] prepare rename annotation module to detection - mapped imports (7294) fkiraly

• [MNT] deduplicate sktime and skbase BaseEstimator (7213) fkiraly

• [MNT] [Dependabot](deps): Update numpy requirement from <2.1,>=1.21 to >=1.21,<2.2 (7103) dependabot[bot]

• [MNT] [Dependabot](deps): Update scikit-base requirement from <0.9.0,>=0.6.1 to >=0.6.1,<0.12.0 (7238) dependabot[bot]

• [MNT] [Dependabot](deps): Update holidays requirement from <0.55,>=0.29 to >=0.29,<0.59 (7308) dependabot[bot]

• [MNT] [Dependabot](deps): Update sphinx-issues requirement from <5.0.0 to <6.0.0 (7307) dependabot[bot]

Documentation

• [DOC] replace documentation references to "annotation" with "detection" (7299) fkiraly

• [DOC] change imports in detection tutorial to detection module (7306) fkiraly

Highlights

new forecaster: interface to Chronos (zero-shot) foundation model forecaster ( #7001 ) @Z-Fran , @geetu040 , @benHeid , @rigvedmanoj

new classifiers: GRU-based time series classifiers ( #6952 ) @fnhirwa

new transformer: temporal radial basis function features ( #7261 ) @phoeenniixx

new ExpandingSlidingWindowSplitter , switching from expanding window to sliding window at cutoff point ( #7193 ) @MarkusSagen

pytorch-forecasting and neuralforecast models now provide probabilistic forecasts for global forecasting ( #6628 , #6666 ) @XinyuWuu

PolynomialTrendForecaster now can make probabilistic forecasts ( #6424 ) @ericjb

TimesFMForecaster now allows to select the source package, and zero-shot usage has been memory optimized ( #7204 , #7212 ) @Prtm2110 , @fkiraly

Dependency changes

skpro (forecasting soft dependency) bounds have been updated to >=2,<2.8.0

u8darts (forecasting soft dependency) bounds have been updated to >=0.29.0,<0.32.0

dask (data container and parallelization back-end soft dependency) bounds have been updated to <2024.10.1

Core interface changes

Performance metrics for probabilistic forecasting, for interval and quantile returns, can now optionally be constructed with an alpha (quantile forecasts) or coverage (interval forecasts) parameter, for example EmpiricalCoverage(coverage=0.7) for “empirical coverage at nominal interval coverage 70 percent”.

These are for use with benchmarking or tuning interfaces, where a metric is provided, but predict_interval or predict_quantiles are not explicitly called.

In such a case, the parameter of the metric will be used by the tuner or benchmark utility to tune with the metric at that quantile alpha or interval coverage .

For example, ForecastingGridSearchCV(fcst, cv, scoring=PinballLoss(alpha=[0.3, 0.7])) , to tune the forecaster fcst scored by the pinball loss at quantiles 0.3 and 0.7.

Enhancements

BaseObject and base framework

[ENH] version tag for objects and estimators ( #3629 ) @fkiraly

[ENH] add test that html repr of objects does not crash ( #7151 ) @fkiraly

[ENH] decorators for singleton and multiton oop pattern ( #7203 ) @fkiraly

Benchmarking, Metrics, Splitters

[ENH] ExpandingSlidingWindowSplitter , switching from expanding window to sliding window at cutoff point ( #7193 ) @MarkusSagen

[ENH] added coverage parameter to all metrics of pred_interval type ( #7278 ) @talat-khattatov

Data types, checks, conversions

[ENH] refactor datatypes module to scikit-base classes and data records ( #7161 ) @fkiraly

[ENH] Fix polars PerformanceWarning when object is of type polars.LazyFrame ( #7221 ) @shivanshsinghal-22

Forecasting

[ENH] Added method predict_interval to PolynomialTrendForecaster ( #6424 ) @ericjb

[ENH] Quantile Forecast for pytorch-forecasting Models with Global Forecast API ( #6628 ) @XinyuWuu

[ENH] Global Forecast API for NeuralForecast interface ( #6666 ) @XinyuWuu

[ENH] testing global forecasters: reduces number of obs in _make_hierarchical for test data generation to ensure shorter runtimes ( #6948 ) @julian-fong

[ENH] interface to Chronos (zero-shot) foundation model forecaster ( #7001 ) @Z-Fran , @geetu040 , @benHeid , @rigvedmanoj

[ENH] Added get_test_params in ThetaLinesTransformer ( #7199 ) @Anuragwagh

[ENH] cached timesfm instance in case of repeated use ( #7204 ) @fkiraly

[ENH] refactor probabilistic prediction default dispatching logic to mixin class ( #7230 ) @fkiraly

[ENH] TimesFMForecaster dependencies now depends on use_source_package ( #7212 ) @Prtm2110

[ENH] python 3.13 compatibility - SquaringResiduals ( #7244 ) @fkiraly

Registry and search

[ENH] python 3.13 compatibility - craft ( #7251 ) @fkiraly

Time series classification

[ENH] GRU-based time series classifiers ( #6952 ) @fnhirwa

Transformations

[ENH] HOG1D Transformer add new test parameter set to get_test_params ( #7183 ) @Humorloos

[ENH] Added second parameters example to get_test_params of Filter ( #7178 ) @KarlKolibri

[ENH] temporal radial basis function feature transformer ( #7261 ) @phoeenniixx

Test framework

[ENH] get_test_params cases in composites conditional on soft dependencies to use _check_estimator_deps ( #7225 ) @shivanshsinghal-22

Documentation

[DOC] Added reference of load-tecator ( #7171 ) @vedantag17

[DOC] Add example to HOG1DTransformer ( #7180 ) @Humorloos

[DOC] add docstring example for PaddingTransformer ( #7179 ) @jan-mue

[DOC] Added docstring example for HurstExponentTransformer ( #7185 ) @Dehelaan

[DOC] add docstring example to Filter transformer ( #7175 ) @fkiraly

[DOC] clearer install instructions ( #7206 ) @fkiraly

[DOC] Added MOIRAIforecaster to the API docs, create new section on pretrained FM ( #7223 ) @Dehelaan

[DOC] improved docstrings for k-nearest neighbours classifier and regressor ( #7241 ) @fkiraly

[DOC] SlidingWindowSplitter - proper mathematical description ( #7195 ) @fkiraly

[DOC] anomaly and changepoint detection notebook from ODSC 2024 ( #7284 ) @alex-jg3 , @fkiraly

[DOC] Fixes Time Series Segmentation with sktime and ClaSP notebook example ( #7283 ) @RobotPsychologist

[DOC] Fixed minor grammatical errors in README.md ( #7262 ) @Smoothengineer

[DOC] added missing import statements in ReverseAugmenter docstring example ( #7265 ) @sanskarmodi8

[DOC] clarify how fh in forecasting methods is interpreted ( #7227 ) @ericjb

Maintenance

[MNT] Removes coverage upload steps from CI ( #7012 ) @Prtm2110

[MNT] Dependabot: Update skpro requirement from <2.6.0,>=2 to >=2,<2.8.0 ( #7245 ) @dependabot[bot]

[MNT] Dependabot: Update sphinx-gallery requirement from <0.18.0 to <0.19.0 ( #7264 ) @dependabot[bot]

[MNT] Dependabot: Update u8darts requirement from <0.31,>=0.29.0 to >=0.29.0,<0.32 ( #7272 ) @dependabot[bot]

[MNT] Dependabot: Update dask requirement from <2024.8.1 to <2024.10.1 ( #7292 ) @dependabot[bot]

Fixes

Benchmarking, Metrics, Splitters

[BUG] Fix ExpandingCutoffSplitter when step_length > 1 ( #7290 ) @ninedigits

Data sets and data loaders

[BUG] skip the test load_fpp3 if rdata is not installed ( #7181 ) @jan-mue

Data types, checks, conversions

[BUG] fixed dask.dataframe import error in dask_to_pd module ( #7260 ) @sanskarmodi8

Forecasting

[BUG] fix ForecastingHorizon.to_absolute with multiple frequencies ( #7172 ) @tianjiqx

[BUG] in ReconcilerForecaster , fix return_totals parameter for all strategies ( #7208 ) @SaiRevanth25

[BUG] Fix DartsLinearRegression failing instead of giving a warning ( #7235 ) @fnhirwa

[BUG] Fix Prophet not tagged as handles-missing-data ( #7267 ) @Garve

[BUG] fix singular matrices in test_reconcilerforecaster_return_totals ( #7293 ) @fkiraly

Contributors

@alex-jg3 , @Anuragwagh , @benHeid , @Dehelaan , @ericjb , @fkiraly , @fnhirwa , @Garve , @geetu040 , @Humorloos , @jan-mue , @julian-fong , @KarlKolibri , @MarkusSagen , @ninedigits , @phoeenniixx , @Prtm2110 , @RobotPsychologist , @rigvedmanoj , @SaiRevanth25 , @sanskarmodi8 , @shivanshsinghal-22 , @Smoothengineer , @talat-khattatov , @tianjiqx , @vedantag17 , @XinyuWuu , @Z-Fran

Highlights

• new forecaster: interface to Chronos (zero-shot) foundation model forecaster (7001) Z-Fran, geetu040, benHeid, rigvedmanoj

• new classifiers: GRU-based time series classifiers (6952) fnhirwa

• new transformer: temporal radial basis function features (7261) phoeenniixx

• new ExpandingSlidingWindowSplitter, switching from expanding window to sliding window at cutoff point (7193) MarkusSagen

• pytorch-forecasting and neuralforecast models now provide probabilistic forecasts for global forecasting (6628, 6666) XinyuWuu

• PolynomialTrendForecaster now can make probabilistic forecasts (6424) ericjb

• TimesFMForecaster now allows to select the source package, and zero-shot usage has been memory optimized (7204, 7212) Prtm2110, fkiraly

Dependency changes

• skpro (forecasting soft dependency) bounds have been updated to >=2,<2.8.0

• u8darts (forecasting soft dependency) bounds have been updated to >=0.29.0,<0.32.0

• dask (data container and parallelization back-end soft dependency) bounds have been updated to <2024.10.1

Core interface changes

Performance metrics for probabilistic forecasting, for interval and quantile returns, can now optionally be constructed with an alpha (quantile forecasts) or coverage (interval forecasts) parameter, for example EmpiricalCoverage(coverage=0.7) for "empirical coverage at nominal interval coverage 70 percent".

These are for use with benchmarking or tuning interfaces, where a metric is provided, but predict_interval or predict_quantiles are not explicitly called.

In such a case, the parameter of the metric will be used by the tuner or benchmark utility to tune with the metric at that quantile alpha or interval coverage.

For example, ForecastingGridSearchCV(fcst, cv, scoring=PinballLoss(alpha=[0.3, 0.7])), to tune the forecaster fcst scored by the pinball loss at quantiles 0.3 and 0.7.

Enhancements

BaseObject and base framework

• [ENH] version tag for objects and estimators (3629) fkiraly

• [ENH] add test that html repr of objects does not crash (7151) fkiraly

• [ENH] decorators for singleton and multiton oop pattern (7203) fkiraly

Benchmarking, Metrics, Splitters

• [ENH] ExpandingSlidingWindowSplitter, switching from expanding window to sliding window at cutoff point (7193) MarkusSagen

• [ENH] added coverage parameter to all metrics of pred_interval type (7278) talat-khattatov

Data types, checks, conversions

• [ENH] refactor datatypes module to scikit-base classes and data records (7161) fkiraly

• [ENH] Fix polars PerformanceWarning when object is of type polars.LazyFrame (7221) shivanshsinghal-22

Forecasting

• [ENH] Added method predict_interval to PolynomialTrendForecaster (6424) ericjb

• [ENH] Quantile Forecast for pytorch-forecasting Models with Global Forecast API (6628) XinyuWuu

• [ENH] Global Forecast API for NeuralForecast interface (6666) XinyuWuu

• [ENH] testing global forecasters: reduces number of obs in _make_hierarchical for test data generation to ensure shorter runtimes (6948) julian-fong

• [ENH] interface to Chronos (zero-shot) foundation model forecaster (7001) Z-Fran, geetu040, benHeid, rigvedmanoj

• [ENH] Added get_test_params in ThetaLinesTransformer (7199) Anuragwagh

• [ENH] cached timesfm instance in case of repeated use (7204) fkiraly

• [ENH] refactor probabilistic prediction default dispatching logic to mixin class (7230) fkiraly

• [ENH] TimesFMForecaster dependencies now depends on use_source_package (7212) Prtm2110

• [ENH] python 3.13 compatibility - SquaringResiduals (7244) fkiraly

Registry and search

• [ENH] python 3.13 compatibility - craft (7251) fkiraly

Time series classification

• [ENH] GRU-based time series classifiers (6952) fnhirwa

Transformations

• [ENH] HOG1D Transformer add new test parameter set to get_test_params (7183) Humorloos

• [ENH] Added second parameters example to get_test_params of Filter (7178) KarlKolibri

• [ENH] temporal radial basis function feature transformer (7261) phoeenniixx

Test framework

• [ENH] get_test_params cases in composites conditional on soft dependencies to use _check_estimator_deps (7225) shivanshsinghal-22

Documentation

• [DOC] Added reference of load-tecator (7171) vedantag17

• [DOC] Add example to HOG1DTransformer (7180) Humorloos

• [DOC] add docstring example for PaddingTransformer (7179) jan-mue

• [DOC] Added docstring example for HurstExponentTransformer (7185) Dehelaan

• [DOC] add docstring example to Filter transformer (7175) fkiraly

• [DOC] clearer install instructions (7206) fkiraly

• [DOC] Added MOIRAIforecaster to the API docs, create new section on pretrained FM (7223) Dehelaan

• [DOC] improved docstrings for k-nearest neighbours classifier and regressor (7241) fkiraly

• [DOC] SlidingWindowSplitter - proper mathematical description (7195) fkiraly

• [DOC] anomaly and changepoint detection notebook from ODSC 2024 (7284) alex-jg3, fkiraly

• [DOC] Fixes Time Series Segmentation with sktime and ClaSP notebook example (7283) RobotPsychologist

• [DOC] Fixed minor grammatical errors in README.md (7262) Smoothengineer

• [DOC] added missing import statements in ReverseAugmenter docstring example (7265) sanskarmodi8

• [DOC] clarify how fh in forecasting methods is interpreted (7227) ericjb

Maintenance

• [MNT] Removes coverage upload steps from CI (7012) Prtm2110

• [MNT] [Dependabot](deps): Update skpro requirement from <2.6.0,>=2 to >=2,<2.8.0 (7245) dependabot[bot]

• [MNT] [Dependabot](deps): Update sphinx-gallery requirement from <0.18.0 to <0.19.0 (7264) dependabot[bot]

• [MNT] [Dependabot](deps): Update u8darts requirement from <0.31,>=0.29.0 to >=0.29.0,<0.32 (7272) dependabot[bot]

• [MNT] [Dependabot](deps): Update dask requirement from <2024.8.1 to <2024.10.1 (7292) dependabot[bot]

Fixes

Benchmarking, Metrics, Splitters

• [BUG] Fix ExpandingCutoffSplitter when step_length > 1 (7290) ninedigits

Data sets and data loaders

• [BUG] skip the test load_fpp3 if rdata is not installed (7181) jan-mue

Data types, checks, conversions

• [BUG] fixed dask.dataframe import error in dask_to_pd module (7260) sanskarmodi8

Forecasting

• [BUG] fix ForecastingHorizon.to_absolute with multiple frequencies (7172) tianjiqx

• [BUG] in ReconcilerForecaster, fix return_totals parameter for all strategies (7208) SaiRevanth25

• [BUG] Fix DartsLinearRegression failing instead of giving a warning (7235) fnhirwa

• [BUG] Fix Prophet not tagged as handles-missing-data (7267) Garve

• [BUG] fix singular matrices in test_reconcilerforecaster_return_totals (7293) fkiraly

Contributors

alex-jg3, Anuragwagh, benHeid, Dehelaan, ericjb, fkiraly, fnhirwa, Garve, geetu040, Humorloos, jan-mue, julian-fong, KarlKolibri, MarkusSagen, ninedigits, phoeenniixx, Prtm2110, RobotPsychologist, rigvedmanoj, SaiRevanth25, sanskarmodi8, shivanshsinghal-22, Smoothengineer, talat-khattatov, tianjiqx, vedantag17, XinyuWuu, Z-Fran

Small feature release for showcase at pydata Paris.

Highlights

interface for MOIRAI foundation model ( #6746 ) @pranavvp16 , @benHeid

GroupbyCategoryForecaster for applying panel forecasting by category or segment ( #7066 ) @felipeangelimvieira

In ReconcilerForecaster , users can now choose to return a dataframe without __total ( #7127 ) @SaiRevanth25

time series segmentation via clustering ( #6782 ) @ankit-1204

logger transformer for logging pipeline inputs and outputs ( #7074 ) @fkiraly

Dependency changes

optuna (hyperparameter optimization soft dependency) bounds have been updated to <4.1

mne (transformations soft dependency) bounds have been updated to >=1.5,<1.9

Enhancements

BaseObject and base framework

[ENH] is_scitype utility for scitype checking, improve support of estimators with multiple object types ( #7143 ) @benHeid

Data types, checks, conversions

[ENH] Hierarchical scitype support for polars ( #6697 ) @pranavvp16

[ENH] refactor datatypes example fixtures to BaseObject classes ( #7133 ) @fkiraly

Forecasting

[ENH] Add interface for MOIRAI foundation model ( #6746 ) @pranavvp16 , @benHeid

[ENH] ThetaForecaster - add one more parameter set ( #7055 ) @fkiraly

[ENH] GroupbyCategoryForecaster for applying panel forecasting by category or segment ( #7066 ) @felipeangelimvieira

[ENH] Adding a parameter to ReconcilerForecaster to return a dataframe without the dunder levels ( #7127 ) @SaiRevanth25

[ENH] add _predict_var in test_pred_int_tag ( #7154 ) @fkiraly

Registry and search

[ENH] retrieval utilities for all functions or classes in a module ( #7089 ) @fkiraly

Time series anomalies, changepoints, segmentation

[ENH] time series segmentation via clustering ( #6782 ) @ankit-1204

Transformations

[ENH] logger transformer for logging pipeline inputs and outputs ( #7074 ) @fkiraly

Documentation

[DOC] correct incorrect bounds mentioned in 0.33.0 changelog ( #7114 ) @fkiraly

[DOC] Added a docstring example to TimeSeriesKernelKMeans ( #7124 ) @Saptarshi-Bandopadhyay

[DOC] update core developers on team page, formatting ( #7140 ) @fkiraly

[DOC] minor documentation fixes ( #7141 ) @fkiraly

[DOC] add quicklinks at top of README box ( #7159 ) @fkiraly

[DOC] remove 2024 elections registration news item ( #7158 ) @fkiraly

[DOC] remove references to nested_univ from extension templates ( #7058 ) @fkiraly

Maintenance

[MNT] Updating pre-commit hooks and corresponding changes ( #7109 ) @yarnabrina

[MNT] Dependabot: Update optuna requirement from <3.7 to <4.1 ( #7104 ) @dependabot[bot]

[MNT] Dependabot: Update mne requirement from <1.8,>=1.5 to >=1.5,<1.9 ( #7129 ) @dependabot[bot]

[MNT] temporarily skip temporian related failure of test_complex_function until #7040 is resolved ( #7147 ) @fkiraly

[MNT] fix FPP3 download link ( #7164 ) @fkiraly , @ericjb

[MNT] bound SignatureTransformer to numpy<2 ( #7163 ) @fkiraly

[MNT] remove ptf install from example notebooks ( #7165 ) @XinyuWuu

[MNT] remove python version bound from pytorch-forecasting based estimators ( #7102 ) @fkiraly

Fixes

Forecasting

[BUG] Fix pykan forecaster ( #7150 ) @benHeid

[BUG] fix probabilistic forecasts if only _predict_var is implemented ( #7153 ) @fkiraly

Transformations

[BUG] fix drop_na and update mode of Differencer transformation ( #7115 ) @fkiraly

Test framework

Contributors

@ankit-1204 , @benHeid , @ericjb , @fkiraly , @pranavvp16 , @SaiRevanth25 , @Saptarshi-Bandopadhyay , @XinyuWuu , @yarnabrina

Small feature release for showcase at pydata Paris.

Highlights

• interface for MOIRAI foundation model (6746) pranavvp16, benHeid

• GroupbyCategoryForecaster for applying panel forecasting by category or segment (7066) felipeangelimvieira

• In ReconcilerForecaster, users can now choose to return a dataframe without __total (7127) SaiRevanth25

• time series segmentation via clustering (6782) ankit-1204

• logger transformer for logging pipeline inputs and outputs (7074) fkiraly

Dependency changes

• optuna (hyperparameter optimization soft dependency) bounds have been updated to <4.1

• mne (transformations soft dependency) bounds have been updated to >=1.5,<1.9

Enhancements

BaseObject and base framework

• [ENH] is_scitype utility for scitype checking, improve support of estimators with multiple object types (7143) benHeid

Data types, checks, conversions

• [ENH] Hierarchical scitype support for polars (6697) pranavvp16

• [ENH] refactor datatypes example fixtures to BaseObject classes (7133) fkiraly

Forecasting

• [ENH] Add interface for MOIRAI foundation model (6746) pranavvp16, benHeid

• [ENH] ThetaForecaster - add one more parameter set (7055) fkiraly

• [ENH] GroupbyCategoryForecaster for applying panel forecasting by category or segment (7066) felipeangelimvieira

• [ENH] Adding a parameter to ReconcilerForecaster to return a dataframe without the dunder levels (7127) SaiRevanth25

• [ENH] add _predict_var in test_pred_int_tag (7154) fkiraly

Registry and search

• [ENH] retrieval utilities for all functions or classes in a module (7089) fkiraly

Time series anomalies, changepoints, segmentation

• [ENH] time series segmentation via clustering (6782) ankit-1204

Transformations

• [ENH] logger transformer for logging pipeline inputs and outputs (7074) fkiraly

Documentation

• [DOC] correct incorrect bounds mentioned in 0.33.0 changelog (7114) fkiraly

• [DOC] Added a docstring example to TimeSeriesKernelKMeans (7124) Saptarshi-Bandopadhyay

• [DOC] update core developers on team page, formatting (7140) fkiraly

• [DOC] minor documentation fixes (7141) fkiraly

• [DOC] add quicklinks at top of README box (7159) fkiraly

• [DOC] remove 2024 elections registration news item (7158) fkiraly

• [DOC] remove references to nested_univ from extension templates (7058) fkiraly

Maintenance

• [MNT] Updating pre-commit hooks and corresponding changes (7109) yarnabrina

• [MNT] [Dependabot](deps): Update optuna requirement from <3.7 to <4.1 (7104) dependabot[bot]

• [MNT] [Dependabot](deps): Update mne requirement from <1.8,>=1.5 to >=1.5,<1.9 (7129) dependabot[bot]

• [MNT] temporarily skip temporian related failure of test_complex_function until #7040 is resolved (7147) fkiraly

• [MNT] fix FPP3 download link (7164) fkiraly, ericjb

• [MNT] bound SignatureTransformer to numpy<2 (7163) fkiraly

• [MNT] remove ptf install from example notebooks (7165) XinyuWuu

• [MNT] remove python version bound from pytorch-forecasting based estimators (7102) fkiraly

Fixes

Forecasting

• [BUG] Fix pykan forecaster (7150) benHeid

• [BUG] fix probabilistic forecasts if only _predict_var is implemented (7153) fkiraly

Transformations

• [BUG] fix drop_na and update mode of Differencer transformation (7115) fkiraly

Test framework

Contributors

ankit-1204, benHeid, ericjb, fkiraly, pranavvp16, SaiRevanth25, Saptarshi-Bandopadhyay, XinyuWuu, yarnabrina

Maintenance release, with scheduled deprecations and change actions.

For last non-maintenance content updates, see 0.32.4 and 0.32.2.

Dependency changes

scikit-base (core dependency) bounds have been updated to >=0.6.1,<0.10.0

holidays (transformations soft dependency) bounds have been updated to >=0.29,<0.57

pykan (deep learning soft dependency) bounds have been updated to >=0.2,<0.2.7

mne (transformations soft dependency) bounds have been updated to >=1.5,<1.9

dask (data container and parallelization back-end soft dependency) bounds have been updated to <2024.8.3

pytorch-forecasting (forecasting soft dependency) bounds have been updated to >=1.0.0,<1.2.0

Deprecations and removals

in DirectReductionForecaster the default for windows_identical has changed to False .

Maintenance

[MNT] Try to reduce load for the runners ( #7061 ) @benHeid

[MNT] 0.33.0 deprecations and change actions ( #7091 ) @fkiraly

[MNT] ffp3 datasets URLs changed on CRAN; updated _fpp3_loaders.py accordingly ( #7084 ) @ericjb

[MNT] remove <3.11 restriction for pytorch-forecasting , add upper bound ( #7092 ) @fkiraly

[MNT] Dependabot: Update dask requirement from <2024.8.2 to <2024.8.3 ( #7062 ) @dependabot[bot]

[MNT] Dependabot: Update numpy requirement from <2.1,>=1.21 to >=1.21,<2.2 ( #7007 ) @dependabot[bot]

[MNT] Dependabot: Update scikit-base requirement from <0.9.0,>=0.6.1 to >=0.6.1,<0.10.0 ( #7035 ) @dependabot[bot]

[MNT] Dependabot: Update holidays requirement from <0.56,>=0.29 to >=0.29,<0.57 ( #7096 ) @dependabot[bot]

[MNT] Dependabot: Update pykan requirement from <0.2.2,>=0.2 to >=0.2,<0.2.7 ( #7010 ) @dependabot[bot]

[MNT] Dependabot: Update mne requirement from <1.8,>=1.5 to >=1.5,<1.9 ( #7004 ) @dependabot[bot]

Documentation

[DOC] Adds @SaiRevanth25` contributions to all-contributors file ( #7085 ) @SaiRevanth25

[DOC] fix typo and formatting in installation docs ( #7060 ) @Saptarshi-Bandopadhyay

Enhancements

[ENH] change test_inheritance to be more lenient to framework level extensions ( #7067 ) @fkiraly

Contributors

@benHeid , @ericjb , @fkiraly , @SaiRevanth25 , @Saptarshi-Bandopadhyay

Maintenance release, with scheduled deprecations and change actions.

For last non-maintenance content updates, see 0.32.4 and 0.32.2.

Dependency changes

• scikit-base (core dependency) bounds have been updated to >=0.6.1,<0.10.0

• holidays (transformations soft dependency) bounds have been updated to >=0.29,<0.57

• pykan (deep learning soft dependency) bounds have been updated to >=0.2,<0.2.7

• mne (transformations soft dependency) bounds have been updated to >=1.5,<1.9

• dask (data container and parallelization back-end soft dependency) bounds have been updated to <2024.8.3

• pytorch-forecasting (forecasting soft dependency) bounds have been updated to >=1.0.0,<1.2.0

Deprecations and removals

• in DirectReductionForecaster the default for windows_identical has changed to False.

Maintenance

• [MNT] Try to reduce load for the runners (7061) benHeid

• [MNT] 0.33.0 deprecations and change actions (7091) fkiraly

• [MNT] ffp3 datasets URLs changed on CRAN; updated _fpp3_loaders.py accordingly (7084) ericjb

• [MNT] remove <3.11 restriction for pytorch-forecasting, add upper bound (7092) fkiraly

• [MNT] [Dependabot](deps): Update dask requirement from <2024.8.2 to <2024.8.3 (7062) dependabot[bot]

• [MNT] [Dependabot](deps): Update numpy requirement from <2.1,>=1.21 to >=1.21,<2.2 (7007) dependabot[bot]

• [MNT] [Dependabot](deps): Update scikit-base requirement from <0.9.0,>=0.6.1 to >=0.6.1,<0.10.0 (7035) dependabot[bot]

• [MNT] [Dependabot](deps): Update holidays requirement from <0.56,>=0.29 to >=0.29,<0.57 (7096) dependabot[bot]

• [MNT] [Dependabot](deps): Update pykan requirement from <0.2.2,>=0.2 to >=0.2,<0.2.7 (7010) dependabot[bot]

• [MNT] [Dependabot](deps): Update mne requirement from <1.8,>=1.5 to >=1.5,<1.9 (7004) dependabot[bot]

Documentation

• [DOC] Adds SaiRevanth25` contributions to all-contributors file (7085) SaiRevanth25

• [DOC] fix typo and formatting in installation docs (7060) Saptarshi-Bandopadhyay

Enhancements

• [ENH] change test_inheritance to be more lenient to framework level extensions (7067) fkiraly

Contributors

benHeid, ericjb, fkiraly, SaiRevanth25, Saptarshi-Bandopadhyay

Small feature and fix release for:

colab compatibility, hotfix for polars dependency incompatibility

compatibility with skchange 2nd party integration

improvements to the anomalies, changepoints, segmentation framework

documentation update related to upcoming sktime elections

Core interface changes

A scitype adaptation framework is introduced, allowing use of an estimator of one type in a slot for another, via type coercion. The coercion framework covers sklearn , skpro , and sktime estimators currently, and is extensible. A user and developer shorthand for such coercion is provided as the registry.coerce_scitype function, which dispatches to individual coercion mechanisms.

Time series clusterers that produce a cluster assignment can be coerced to transformations, enabling their use in any pipeline slot for transformations.

Anomaly and changepoint detectors can now be pipelined with transformations, resulting in a detector. Dunder concatenation transformer * detector will default to this.

Anomaly and changepoint detectors can be coerced to transformations, enabling their use in any pipeline slot for transformations.

Enhancements

BaseObject and base framework

[ENH] decouple registry from base modules, scitype specific data records for documentation of estimator types ( #6998 ) @fkiraly

[ENH] scitype coercion and checking utility ( #6969 ) @fkiraly

Time series anomalies, changepoints, segmentation

[ENH] Add padded f1 score for evaluating change point detection algorithms ( #7034 ) @Alex-JG3

[ENH] improvements to BaseSeriesAnnotator base class for anomaly, changepoint, segments ( #7073 ) @fkiraly

[ENH] pipeline for anomaly, changepoint detectors and segmenters ( #7071 ) @fkiraly

[ENH] coercion to use time series anomaly, changepoint detectors as transformers ( #7072 ) @fkiraly

Time series clustering

[ENH] enable use of clusterers as transformations, enable TransformSelectForecaster use of clusterers for group selection ( #7068 ) @fkiraly

Transformations

[ENH] Hurst exponent feature extraction transformer ( #7065 ) @phoeenniixx

Documentation

[DOC] Add SVG version of the sktime logo with no text ( #7024 ) @wirrywoo

[DOC] Improve documentation for TinyTimeMixer ( #7009 ) @geetu040

[DOC] fix broken links in continuous integration docs ( #7059 ) @Saptarshi-Bandopadhyay

[DOC] split list of transformation pipeline components into subcategories ( #7075 ) @fkiraly

Fixes

[BUG] fix sktime crash with older polars versions ( #7057 ) @fkiraly

[BUG] Fix ForecastX.update when the forecaster_X_exogeneous is set to "complement" ( #7041 ) @fnhirwa

[BUG] fix ExpandingCutoffSplitter for case where fh is not continuous ( #7053 ) @ninedigits

Contributors

@Alex-JG3 , @fkiraly , @fnhirwa , @geetu040 , @ninedigits , @phoeenniixx , @Saptarshi-Bandopadhyay , @wirrywoo

Small feature and fix release for:

• colab compatibility, hotfix for polars dependency incompatibility

• compatibility with skchange 2nd party integration

• improvements to the anomalies, changepoints, segmentation framework

• documentation update related to upcoming sktime elections

Core interface changes

• A scitype adaptation framework is introduced, allowing use of an estimator of one type in a slot for another, via type coercion. The coercion framework covers sklearn, skpro, and sktime estimators currently, and is extensible. A user and developer shorthand for such coercion is provided as the registry.coerce_scitype function, which dispatches to individual coercion mechanisms.

• Time series clusterers that produce a cluster assignment can be coerced to transformations, enabling their use in any pipeline slot for transformations.

• Anomaly and changepoint detectors can now be pipelined with transformations, resulting in a detector. Dunder concatenation transformer * detector will default to this.

• Anomaly and changepoint detectors can be coerced to transformations, enabling their use in any pipeline slot for transformations.

Enhancements

BaseObject and base framework

• [ENH] decouple registry from base modules, scitype specific data records for documentation of estimator types (6998) fkiraly

• [ENH] scitype coercion and checking utility (6969) fkiraly

Time series anomalies, changepoints, segmentation

• [ENH] Add padded f1 score for evaluating change point detection algorithms (7034) Alex-JG3

• [ENH] improvements to BaseSeriesAnnotator base class for anomaly, changepoint, segments (7073) fkiraly

• [ENH] pipeline for anomaly, changepoint detectors and segmenters (7071) fkiraly

• [ENH] coercion to use time series anomaly, changepoint detectors as transformers (7072) fkiraly

Time series clustering

• [ENH] enable use of clusterers as transformations, enable TransformSelectForecaster use of clusterers for group selection (7068) fkiraly

Transformations

• [ENH] Hurst exponent feature extraction transformer (7065) phoeenniixx

Documentation

• [DOC] Add SVG version of the sktime logo with no text (7024) wirrywoo

• [DOC] Improve documentation for TinyTimeMixer (7009) geetu040

• [DOC] fix broken links in continuous integration docs (7059) Saptarshi-Bandopadhyay

• [DOC] split list of transformation pipeline components into subcategories (7075) fkiraly

Fixes

• [BUG] fix sktime crash with older polars versions (7057) fkiraly

• [BUG] Fix ForecastX.update when the forecaster_X_exogeneous is set to "complement" (7041) fnhirwa

• [BUG] fix ExpandingCutoffSplitter for case where fh is not continuous (7053) ninedigits

Contributors

Alex-JG3, fkiraly, fnhirwa, geetu040, ninedigits, phoeenniixx, Saptarshi-Bandopadhyay, wirrywoo

Hotfix release with bugfix for html representation of forecasting pipelines.

For last non-maintenance content updates, see 0.32.2.

Contents

[BUG] fix html display for TransformedTargetForecaster and ForecastingPipeline

Highlights

HierarchicalProphet forecaster from prophetverse ( #7028 ) @felipeangelimvieira

Regularized VAR reduction forecaster, VARReduce ( #6725 ) @meraldoantonio

Interface to TimesFM Forecaster ( #6571 ) @geetu040

Subsequence Extraction Transformer ( #6967 ) @wirrywoo

Framework support for categorical data has been extended to transformers and pipelines ( #6924 ) @Abhay-Lejith

Clusterer tags for capability to assign cluster centers ( #7018 ) @fkiraly

Dependency changes

holiday (transformations soft dependency) bounds have been updated to >=0.29,<0.56

dask (data container and parallelization back-end) bounds have been updated to <2024.8.2

Core interface changes

New tags for clusterers have been added to characterize capabilities to assign cluster centers. The following boolean tags have been added:

capability:predict , whether the clusterer can assign cluster labels via predict

capability:predict_proba , for probabilistic cluster assignment

capability:out_of_sample , for out-of-sample cluster assignment. If False, the clusterer can only assign clusters to data points seen during fitting.

Enhancements

BaseObject and base framework

[ENH] placeholder record decorator ( #7029 ) @fkiraly

Data sets and data loaders

[ENH] Hierarchical sales toydata generator from workshops ( #6953 ) @marrov

[ENH] Convert the date column to a period with daily frequency in load_m5 ( #6990 ) @SaiRevanth25

Data types, checks, conversions

[ENH] Polars Series scitype supports ( #6485 ) @pranavvp16

[ENH] Polars Panel scitype support ( #6552 ) @pranavvp16

[ENH] Addition of feature_kind metadata attribute to gluonts datatypes ( #6871 ) @shlok191

Forecasting

[ENH] interface to TimesFM Forecaster ( #6571 ) @geetu040

[ENH] New regularized VAR reduction forecaster, VARReduce ( #6725 ) @meraldoantonio

[ENH] Add HierarchicalProphet estimator to prophetverse module ( #7028 ) @felipeangelimvieira

Time series clustering

[ENH] clusterer tags for capability to assign cluster centers ( #7018 ) @fkiraly

Transformations

[ENH] Extending categorical support in X to transformers and pipelines ( #6924 ) @Abhay-Lejith

[ENH] Subsequence Extraction Transformer ( #6967 ) @wirrywoo

Documentation

[DOC] minor improvements to docstring of Bollinger (bands) ( #6978 ) @fkiraly

[DOC] Update .all-contributorsrc with council roles ( #6962 ) @fkiraly

[DOC] update soft dependency handling guide for estimators ( #7000 ) @fkiraly

[DOC] improvements to docstrings for panel tasks - time series classification, regression, clustering ( #6991 ) @fkiraly

[DOC] update XinyuWuu’s user name ( #7030 ) @fkiraly

[DOC] fixes to TransformedTargetForecaster docstring ( #7002 ) @fkiraly

[DOC] update intro notebook with material from ISF and EuroSciPy 2024 ( #7013 ) @fkiraly

[DOC] Fix docstring for ExpandingCutoffSplitter ( #7033 ) @ninedigits

[DOC] fix incorrect import in EnbPIForecaster docstring ( #7015 ) @fkiraly

Maintenance

[MNT] Refactor show_versions to use dependencies module ( #6883 ) @fkiraly

[MNT] sync changelog with hotfix branch anirban-sktime-0.31.2 ( #6963 ) @yarnabrina

[MNT] add numpy 2 incompatibility flag to pmdarima dependency ( #6974 ) @fkiraly

[MNT] decorate test_auto_arima with numpy 2 skip until final fix/diagnosis ( #6973 ) @fkiraly

[MNT] remove tsbootstrap dependency from public dependency sets ( #6966 ) @fkiraly

[MNT] rename base class TimeSeriesLloyds to BaseTimeSeriesLloyds ( #6992 ) @fkiraly

[MNT] remove module level numba import warnings ( #6999 ) @fkiraly

[MNT] esig based estimators: add numpy<2 bound ( #7036 ) @fkiraly

[MNT] Dependabot: Bump tj-actions/changed-files from 44 to 45 ( #7019 ) @dependabot[bot]

[MNT] Dependabot: Update holidays requirement from <0.55,>=0.29 to >=0.29,<0.56 ( #7006 ) @dependabot[bot]

[MNT] Dependabot: Update dask requirement from <2024.8.1 to <2024.8.2 ( #7005 ) @dependabot[bot]

Fixes

BaseObject and base framework

[BUG] fix test_softdep_error dependency handling check if environment marker tag is not satisfied ( #6961 ) @fkiraly

[BUG] fix dependency checkers in case of multiple distributions available in environment, e.g., on databricks ( #6986 ) @fkiraly , @toandaominh1997

Benchmarking and Metrics

[BUG] Fix ForecastingBenchmark giving an error when the dataloader returns the tuple (y, X) ( #6971 ) @SaiRevanth25

Data sets and data loaders

Data types, checks, conversions

[BUG] Fix nested_univ converter inconsistent handling of index level names ( #7026 ) @pranavvp16

Forecasting

[BUG] TinyTimeMixerForecaster : fix truncating index and update test_params ( #6965 ) @geetu040

[BUG] Do not add season condition names as extra regressors in Prophet ( #6988 ) @wpdonders

[BUG] Fix Prophet _get_fitted_params error when the timeseries is constant ( #7011 ) @felipeangelimvieira

Contributors

@Abhay-Lejith , @felipeangelimvieira , @fkiraly , @geetu040 , @marrov , @meraldoantonio , @ninedigits , @pranavvp16 , @SaiRevanth25 , @shlok191 , @toandaominh1997 , @wirrywoo , @wpdonders , @yarnabrina

Highlights

• HierarchicalProphet forecaster from prophetverse (7028) felipeangelimvieira

• Regularized VAR reduction forecaster, VARReduce (6725) meraldoantonio

• Interface to TimesFM Forecaster (6571) geetu040

• Subsequence Extraction Transformer (6967) wirrywoo

• Framework support for categorical data has been extended to transformers and pipelines (6924) Abhay-Lejith

• Clusterer tags for capability to assign cluster centers (7018) fkiraly

Dependency changes

• holiday (transformations soft dependency) bounds have been updated to >=0.29,<0.56

• dask (data container and parallelization back-end) bounds have been updated to <2024.8.2

Core interface changes

New tags for clusterers have been added to characterize capabilities to assign cluster centers. The following boolean tags have been added:

• capability:predict, whether the clusterer can assign cluster labels via predict

• capability:predict_proba, for probabilistic cluster assignment

• capability:out_of_sample, for out-of-sample cluster assignment. If False, the clusterer can only assign clusters to data points seen during fitting.

Enhancements

BaseObject and base framework

• [ENH] placeholder record decorator (7029) fkiraly

Data sets and data loaders

• [ENH] Hierarchical sales toydata generator from workshops (6953) marrov

• [ENH] Convert the date column to a period with daily frequency in load_m5 (6990) SaiRevanth25

Data types, checks, conversions

• [ENH] Polars Series scitype supports (6485) pranavvp16

• [ENH] Polars Panel scitype support (6552) pranavvp16

• [ENH] Addition of feature_kind metadata attribute to gluonts datatypes (6871) shlok191

Forecasting

• [ENH] interface to TimesFM Forecaster (6571) geetu040

• [ENH] New regularized VAR reduction forecaster, VARReduce (6725) meraldoantonio

• [ENH] Add HierarchicalProphet estimator to prophetverse module (7028) felipeangelimvieira

Time series clustering

• [ENH] clusterer tags for capability to assign cluster centers (7018) fkiraly

Transformations

• [ENH] Extending categorical support in X to transformers and pipelines (6924) Abhay-Lejith

• [ENH] Subsequence Extraction Transformer (6967) wirrywoo

Documentation

• [DOC] minor improvements to docstring of Bollinger (bands) (6978) fkiraly

• [DOC] Update .all-contributorsrc with council roles (6962) fkiraly

• [DOC] update soft dependency handling guide for estimators (7000) fkiraly

• [DOC] improvements to docstrings for panel tasks - time series classification, regression, clustering (6991) fkiraly

• [DOC] update XinyuWuu's user name (7030) fkiraly

• [DOC] fixes to TransformedTargetForecaster docstring (7002) fkiraly

• [DOC] update intro notebook with material from ISF and EuroSciPy 2024 (7013) fkiraly

• [DOC] Fix docstring for ExpandingCutoffSplitter (7033) ninedigits

• [DOC] fix incorrect import in EnbPIForecaster docstring (7015) fkiraly

Maintenance

• [MNT] Refactor show_versions to use dependencies module (6883) fkiraly

• [MNT] sync changelog with hotfix branch anirban-sktime-0.31.2 (6963) yarnabrina

• [MNT] add numpy 2 incompatibility flag to pmdarima dependency (6974) fkiraly

• [MNT] decorate test_auto_arima with numpy 2 skip until final fix/diagnosis (6973) fkiraly

• [MNT] remove tsbootstrap dependency from public dependency sets (6966) fkiraly

• [MNT] rename base class TimeSeriesLloyds to BaseTimeSeriesLloyds (6992) fkiraly

• [MNT] remove module level numba import warnings (6999) fkiraly

• [MNT] esig based estimators: add numpy<2 bound (7036) fkiraly

• [MNT] [Dependabot](deps): Bump tj-actions/changed-files from 44 to 45 (7019) dependabot[bot]

• [MNT] [Dependabot](deps): Update holidays requirement from <0.55,>=0.29 to >=0.29,<0.56 (7006) dependabot[bot]

• [MNT] [Dependabot](deps): Update dask requirement from <2024.8.1 to <2024.8.2 (7005) dependabot[bot]

Fixes

BaseObject and base framework

• [BUG] fix test_softdep_error dependency handling check if environment marker tag is not satisfied (6961) fkiraly

• [BUG] fix dependency checkers in case of multiple distributions available in environment, e.g., on databricks (6986) fkiraly, toandaominh1997

Benchmarking and Metrics

• [BUG] Fix ForecastingBenchmark giving an error when the dataloader returns the tuple (y, X) (6971) SaiRevanth25

Data sets and data loaders

Data types, checks, conversions

• [BUG] Fix nested_univ converter inconsistent handling of index level names (7026) pranavvp16

Forecasting

• [BUG] TinyTimeMixerForecaster: fix truncating index and update test_params (6965) geetu040

• [BUG] Do not add season condition names as extra regressors in Prophet (6988) wpdonders

• [BUG] Fix Prophet ``_get_fitted_params ``error when the timeseries is constant (7011) felipeangelimvieira

Contributors

Abhay-Lejith, felipeangelimvieira, fkiraly, geetu040, marrov, meraldoantonio, ninedigits, pranavvp16, SaiRevanth25, shlok191, toandaominh1997, wirrywoo, wpdonders, yarnabrina

Hotfix release for using make_reduction with not fully sklearn compliant tabular regressors such as from catboost .

For last non-maintenance content updates, see 0.31.1.

Contents

[BUG] fix make_reduction type inference for non-sklearn estimators

Maintenance release, with scheduled deprecations and change actions.

For last non-maintenance content updates, see 0.31.1.

Dependency changes

skpro (soft dependency) bounds have been updated to >=2,<2.6.0

skforecast (forecasting soft dependency) bounds have been updated to <0.14.0 .

Core interface changes

all sktime estimators and objects are now required to have at least two test parameter sets in get_test_params to be compliant with check_estimator contract tests. This requirement was previously stated in the extension template but not enforced. It is now also included in the automated tests via check_estimator . Estimators without (unreserved) parameters, i.e., where two distinct parameter sets are not possible, are excepted from this.

Deprecations and removals

From sktime 0.38.0 , forecasters’ predict_proba will require skpro to be present in the python environment, for distribution objects to represent distributional forecasts. Until sktime 0.35.0 , predict_proba will continue working without skpro , defaulting to return objects in sktime.proba if skpro is not present. From sktime 0.35.0 , an error will be raised upon call of forecaster predict_proba if skpro is not present in the environment. Users of forecasters’ predict_proba should ensure that skpro is installed in the environment.

The probability distributions module sktime.proba deprecated and will be fully replaced by skpro in sktime 0.38.0 . Until sktime 0.38.0 , imports from sktime.proba will continue working, defaulting to sktime.proba if skpro is not present, otherwise redirecting imports to skpro objects. From sktime 0.35.0 , an error will be raised if skpro is not present in the environment, otherwise imports are redirected to skpro . Direct or indirect users of sktime.proba should ensure skpro is installed in the environment. Direct users of the sktime.proba module should, in addition, replace any imports from sktime.proba with imports from skpro.distributions .

Contents

[MNT] 0.32.0 deprecations and change actions ( #6916 ) @fkiraly

[MNT] Dependabot: Update skpro requirement from <2.5.0,>=2 to >=2,<2.6.0 ( #6897 ) @dependabot[bot]

[MNT] remove numpy 2 incompatibility flag from numba based estimators ( #6915 ) @fkiraly

[MNT] isolate joblib ( #6385 ) @fkiraly

[MNT] handle more pandas deprecations ( #6941 ) @fkiraly

[MNT] deprecation of proba module in favour of skpro soft dependency ( #6940 ) @fkiraly

[MNT] update versions of pre-commit hooks ( #6947 ) @yarnabrina

[MNT] 0.32.0 release action - revert temporary skip get_test_params number check for 0.21.1 and 0.22.0 release ( #5114 ) @fkiraly

[MNT] Bump skforecast to 0.13 version allowing support for python 3.12 ( #6946 ) @yarnabrina

[BUG] Fix Xt_msg type in transformations.base ( #6944 ) @hliebert

Contributors

@fkiraly , @hliebert , @yarnabrina

Maintenance release, with scheduled deprecations and change actions.

For last non-maintenance content updates, see 0.31.1.

Dependency changes

• skpro (soft dependency) bounds have been updated to >=2,<2.6.0

• skforecast (forecasting soft dependency) bounds have been updated to <0.14.0.

Core interface changes

• all sktime estimators and objects are now required to have at least two test parameter sets in get_test_params to be compliant with check_estimator contract tests. This requirement was previously stated in the extension template but not enforced. It is now also included in the automated tests via check_estimator. Estimators without (unreserved) parameters, i.e., where two distinct parameter sets are not possible, are excepted from this.

Deprecations and removals

• From sktime 0.38.0, forecasters' predict_proba will require skpro to be present in the python environment, for distribution objects to represent distributional forecasts. Until sktime 0.35.0, predict_proba will continue working without skpro, defaulting to return objects in sktime.proba if skpro is not present. From sktime 0.35.0, an error will be raised upon call of forecaster predict_proba if skpro is not present in the environment. Users of forecasters' predict_proba should ensure that skpro is installed in the environment.

• The probability distributions module sktime.proba deprecated and will be fully replaced by skpro in sktime 0.38.0. Until sktime 0.38.0, imports from sktime.proba will continue working, defaulting to sktime.proba if skpro is not present, otherwise redirecting imports to skpro objects. From sktime 0.35.0, an error will be raised if skpro is not present in the environment, otherwise imports are redirected to skpro. Direct or indirect users of sktime.proba should ensure skpro is installed in the environment. Direct users of the sktime.proba module should, in addition, replace any imports from sktime.proba with imports from skpro.distributions.

Contents

• [MNT] 0.32.0 deprecations and change actions (6916) fkiraly

• [MNT] [Dependabot](deps): Update skpro requirement from <2.5.0,>=2 to >=2,<2.6.0 (6897) dependabot[bot]

• [MNT] remove numpy 2 incompatibility flag from numba based estimators (6915) fkiraly

• [MNT] isolate joblib (6385) fkiraly

• [MNT] handle more pandas deprecations (6941) fkiraly

• [MNT] deprecation of proba module in favour of skpro soft dependency (6940) fkiraly

• [MNT] update versions of pre-commit hooks (6947) yarnabrina

• [MNT] 0.32.0 release action - revert temporary skip get_test_params number check for 0.21.1 and 0.22.0 release (5114) fkiraly

• [MNT] Bump skforecast to 0.13 version allowing support for python 3.12 (6946) yarnabrina

• [BUG] Fix Xt_msg type in transformations.base (6944) hliebert

Contributors

fkiraly, hliebert, yarnabrina

Hotfix release, released after hotfix release 0.32.1, to apply the same hotfix to 0.31.X versions as well.

Hotfix for using make_reduction with not fully sklearn compliant tabular regressors such as from catboost .

For last non-maintenance content updates, see 0.31.1.

Contents

[BUG] fix make_reduction type inference for non-sklearn estimators

Notes

This is a hotfix for 0.31.1 release, fixing a regression. This release is not contained in the 0.32.0 or 0.32.1 releases.

Highlights

html representation of objects now has a button linking to documentation page ( #6876 ) @mateuszkasprowicz

interface to TinyTimeMixer foundation model ( #6712 ) @geetu040

interface to autots ensemble ( #5948 ) @MBristle

interface to darts reduction models ( #6712 ) @fnhirwa , @yarnabrina

LTSFTransformer based on cure-lab research code base ( #6202 ) @geetu040

MVTS transformer classifier ( #6791 ) @geetu040

forecasters can now support categorical X , as per tag ( #6704 , #6732 ) @Abhay-Lejith

DirectReductionForecaster now has a windows_identical option ( #6650 ) @hliebert

ForecastingOptunaSearchCV can now be passed custom samplers and “higher is better” scores ( #6823 , #6846 ) @bastisar , @gareth-brown-86 , @mk406

Dependency changes

holiday (transformations soft dependency) bounds have been updated to >=0.29,<0.54

dask (data container and parallelization back-end) bounds have been updated to <2024.8.1

Core interface changes

BaseObject and base framework

implementers no longer need to set the package_import_alias tag when estimator dependencies have a different import name than the PEP 440 package name. All internal logic now only uses the PEP 440 package name. There is no need to remove the tag if already set, but it is no longer required.

estimators now have a tag capability:categorical_in_X: bool to indicate that the estimator can handle categorical features in the input data X . Such estimator can be used with categorical and string-valued features if X is passed in one of the pandas based mtypes.

the html representation of all objects now includes a link to the documentation of the object, and is now in line with the sklearn html representation.

Enhancements

BaseObject and base framework

[ENH] improved environment package version check ( #6776 ) @fkiraly

[ENH] Remove package import alias related internal logic and tags ( #6821 ) @fkiraly

[ENH] Adding tag for categorical support in X ( #6704 ) @Abhay-Lejith

[ENH] Adding categorical support: Raising error in yes/no case ( #6732 ) @Abhay-Lejith

[ENH] Link to docs in object’s html repr ( #6876 ) @mateuszkasprowicz

Data sets and data loaders

[ENH] Data Loader for M5 dataset ( #6731 ) @SaiRevanth25

Data types, checks, conversions

[ENH] check_pdmultiindex_panel to return names of invalid object columns if there are any ( #6797 ) @SaiRevanth25

[ENH] Allow object dtype in series ( #5886 ) @yarnabrina

[ENH] converter framework tests in datatypes to cover all types, including those requiring soft dependencies ( #6838 ) @fkiraly

[ENH] add missing feature_kind metadata fields to gluonts based data container checkers ( #6861 ) @fkiraly

[ENH] added feature_kind metadata in datatype checks ( #6490 ) @Abhay-Lejith

[ENH] Adding support for gluonts PandasDataset object ( #6668 ) @shlok191

[ENH] Added support for gluonts PandasDataset as a Series scitype ( #6837 ) @shlok191

Forecasting

[ENH] interface to autots ensemble ( #5948 ) @MBristle

[ENH] darts Reduction Models adapter ( #6712 ) @fnhirwa , @yarnabrina

[ENH] Extension Template For Global Forecasting API ( #6699 ) @XinyuWuu

[ENH] enable multivariate data passed to autots interface ( #6805 ) @fkiraly

[ENH] Add Sampler to ForecastingOptunaSearchCV ( #6823 ) @bastisar

[ENH] Improve TestAllGlobalForecasters ( #6845 ) @XinyuWuu

[ENH] Add scoring direction to ForecastingOptunaSearchCV ( #6846 ) @gareth-brown-86 , @mk406

[ENH] de-novo implementation of LTSFTransformer based on cure-lab research code base ( #6202 ) @geetu040

[ENH] Add windows_identical to DirectReductionForecaster ( #6650 ) @hliebert

[ENH] updates type inference in make_reduction to use central scitype inference and allow proba tabular regressors ( #6893 ) @fkiraly

[ENH] DeepAR and NHiTS and refinements for pytorch-forecasting interface ( #6551 ) @XinyuWuu

[ENH] Interface to TinyTimeMixer foundation model ( #6712 ) @geetu040

[ENH] remove now superfluous try-excepts in forecasting API test suite ( #6906 ) @fkiraly

[ENH] improve test_global_forecasting_tag ( #6929 ) @geetu040

Registry and search

[ENH] in estimator html repr, make version retrieval safer and more flexible ( #6923 ) @fkiraly

Time series anomalies, changepoints, segmentation

[ENH] time series annotation (outliers, changepoints) - test class and full check_estimator integration ( #6843 ) @fkiraly

[ENH] Add Windowed Local Outlier Factor Anomaly Detector ( #6524 ) @Alex-JG3

[ENH] Add binary segmentation annotator for change point detection ( #6723 ) @Alex-JG3

Time series classification

[ENH] Pytorch Classifier intermediate base class for TSC ( #6791 ) @geetu040

[ENH] MVTS transformer classifier ( #6791 ) @geetu040

Transformations

[ENH] add second test params dict to Aggregator ( #6759 ) @fr1ll

[ENH] pandas inner type and global pooling for TabularToSeriesAdaptor ( #6752 ) @fkiraly

[ENH] alternative returns for VmdTransformer - mode spectra and central frequencies ( #6857 ) @fkiraly

[ENH] simplify dictionaries and alias handling in Catch22 ( #6104 ) @fkiraly

[ENH] making self._is_vectorized access more defensive in BaseTransformer ( #6863 ) @fkiraly

Test framework

[ENH] make pyproject.toml parsing for differential testing more robust against non-package relevant changes ( #6882 ) @fkiraly

Vendor and onboard libraries

[ENH] Vendor fracdiff library ( #6777 ) @DinoBektesevic

[ENH] improvements to vendored fracdiff library ( #6912 ) @fkiraly

Documentation

[DOC] Notebook and Template For Global Forecasting API ( #6699 ) @XinyuWuu

[DOC] Add authorship credits to MatrixProfileTransformer for Stumpy authors ( #6762 ) @alexander-lakocy

[DOC] add examples to StatsForecastGARCH and StatsForecastARCH docstrings ( #6761 ) @melinny

[DOC] Add alignment notebook example ( #6768 ) @alexander-lakocy

[DOC] fix transformers type table in API reference in accordance with sphinx guidelines ( #6771 ) @alexander-lakocy

[DOC] Modify editable install to make cross-platform ( #6758 ) @fr1ll

[DOC] TruncationTransformer docstring example ( #6765 ) @ceroper

[DOC] De-duplicate User Guide and Examples (closes #6767) ( #6770 ) @alexander-lakocy

[DOC] improved docstring of DWTTransformer ( #6764 ) @Mitchjkjkjk

[DOC] various improvements to user journey on documentation page ( #6760 ) @fkiraly

[DOC] Time series k means max iter parameter docstring ( #6726 ) @AlexeyOm

[DOC] cross-reference estimator search from tags API reference ( #6816 ) @fkiraly , @yarnabrina

[DOC] updated docstring for check_is_mtype to match skpro check_is_mtype function ( #6835 ) @julian-fong

[DOC] example & tutorial notebooks: normalize execution counts, indentation, execute all cells ( #6847 ) @fkiraly

[DOC] clarify column handling in docstring of FourierFeatures ( #6834 ) @fkiraly

[DOC] added fork usage recommendations ( #6827 ) @yarnabrina

[DOC] change links in documentation to refer to same version ( #6841 ) @yarnabrina

[DOC] minor improvements to check_scoring docstring ( #6877 ) @fkiraly

[DOC] add proper author credits to 1:1 interface classes - aligners, distances, forecasters, parameter estimators ( #6850 ) @fkiraly

[DOC] fix docstring formatting of evaluate ( #6864 ) @fkiraly

[DOC] Add documentation for benchmarking module ( #6792 ) @benHeid

[DOC] add elections link on landing page ( #6910 ) @fkiraly

[DOC] Add example notebook for the graphical pipeline ( #5175 ) @benHeid

[DOC] git workflow guide - chained branches, fixing header fonts ( #6913 ) @fkiraly

Maintenance

[MNT] Remove tbats python version constraint ( #6769 ) @fr1ll

[MNT] Update Callable import from typing to collections.abc ( #6798 ) @yarnabrina

[MNT] Fix spellings using codespell and typos ( #6799 ) @yarnabrina

[MNT] improved environment package version check ( #6776 ) @fkiraly

[MNT] downgrade pykan version to <0.2.2 ( #6853 ) @geetu040

[MNT] add non-unicode characters check to the linter ( #6807 ) @fnhirwa

[MNT] updates and fixes to type hints ( #6743 ) @ZhipengXue97

[MNT] Resolve the issue with diacritics failing to be decoded on Windows ( #6862 ) @fnhirwa

[MNT] sync docstring and code formatting of dependency checker module with skbase ( #6873 ) @fkiraly

[MNT] Remove package import alias related internal logic and tags ( #6821 ) @fkiraly

[MNT] restrict failing Mr-SEQL version ( #6879 ) @fkiraly

[MNT] release workflow: Upgrade deprecated pypa action parameter ( #6878 ) @szepeviktor

[MNT] Fix pykan import and dependency checks ( #6881 ) @fkiraly

[MNT] temporarily pin matplotlib below 3.9.1 ( #6890 ) @yarnabrina

[MNT] make pyproject.toml parsing for differential testing more robust against non-package relevant changes ( #6882 ) @fkiraly

[MNT] formatter for jupyter notebook json in build tools ( #6849 ) @fkiraly

[MNT] sync differential testing utilities with skpro ( #6840 ) @fkiraly

[MNT] Handle deprecations from pandas ( #6855 ) @fkiraly

[MNT] sync docstring and code formatting of dependency checker module with skbase ( #6873 ) @fkiraly

[MNT] fix .all-contributorsrc syntax ( #6918 ) @fkiraly

[MNT] Resolve the issue with diacritics failing to be decoded on Windows ( #6862 ) @fnhirwa

[MNT] changelog utility: fix termination condition to retrieve merged PR ( #6920 ) @fkiraly

[MNT] restore holidays lower bound to 0.29 ( #6921 ) @fkiraly

[MNT] Updating the GHA dependencies to install OSX dependencies and setting the compiler flags ( #6926 ) @fnhirwa

[MNT] revert an erroneous instance of pandas deprecation fix ( #6925 ) @fkiraly

[MNT] Update the path to script to fix #6926 ( #6933 ) @fnhirwa

[MNT] Dependabot: Update pytest requirement from <8.3,>=7.4 to >=7.4,<8.4 ( #6819 ) @dependabot[bot]

[MNT] Dependabot: Update dask requirement from <2024.6.3 to <2024.7.2 ( #6818 ) @dependabot[bot]

[MNT] Dependabot: Update sphinx-gallery requirement from <0.17.0 to <0.18.0 ( #6820 ) @dependabot[bot]

[MNT] Dependabot: Update holidays requirement from <0.53,>=0.52 to >=0.52,<0.54 ( #6780 ) @dependabot[bot]

[MNT] Dependabot: Update sphinx requirement from !=7.2.0,<8.0.0 to !=7.2.0,<9.0.0 ( #6865 ) @dependabot[bot]

[MNT] Dependabot: Update holidays requirement from <0.54,>=0.52 to >=0.52,<0.55 ( #6898 ) @dependabot[bot]

[MNT] Dependabot: Update dask requirement from <2024.7.2 to <2024.8.1 ( #6907 ) @dependabot[bot]

Fixes

BaseObject and base framework

[BUG] fix _check_soft_dependencies for post and pre versions of patch versions ( #6909 ) @fkiraly

Data types, checks, conversions

[BUG] fix type inconsistency in conversion pandas to xarray based Series ( #6856 ) @fkiraly

Forecasting

[BUG] Fix pykan dependency and set lower bound ( #6789 ) @benHeid

[BUG] correct dependency tag for pytorch-forecasting forecasters: rename pytorch_forecasting to correct package name pytorch-forecasting ( #6830 ) @XinyuWuu

Registry and search

[BUG] fix polymorphic estimators missing in estimator overview, e.g., pytorch-forecasting forecasters ( #6803 ) @fkiraly

Time series anomalies, changepoints, segmentation

[BUG] Fix bug when predicting segments from clasp change point annotator ( #6756 ) @Alex-JG3

Transformations

[BUG] Refactor ADICVTransformer and fix CV calculation ( #6757 ) @sbhobbes

[BUG] fix BaseTransformer broadcasting condition in inverse_transform for decomposers ( #6824 ) @fkiraly

[BUG] fix MSTL inverse transform and use in forecasting pipeline ( #6825 ) @fkiraly

[BUG] fix handling of numpy integers in refactored Catch22 transformation ( #6934 ) @fkiraly

Visualization

[BUG] In plot_series , trim unused levels when verifying dataframe formatting ( #6754 ) @SultanOrazbayev

Contributors

@Abhay-Lejith , @Alex-JG3 , @alexander-lakocy , @AlexeyOm , @bastisar , @benHeid , @ceroper , @DinoBektesevic , @fkiraly , @fnhirwa , @fr1ll , @gareth-brown-86 , @geetu040 , @hliebert , @julian-fong , @mateuszkasprowicz , @MBristle , @melinny , @Mitchjkjkjk , @mk406 , @SaiRevanth25 , @sbhobbes , @shlok191 , @SultanOrazbayev , @szepeviktor , @XinyuWuu , @yarnabrina , @ZhipengXue97

Highlights

• html representation of objects now has a button linking to documentation page (6876) mateuszkasprowicz

• interface to TinyTimeMixer foundation model (6712) geetu040

• interface to autots ensemble (5948) MBristle

• interface to darts reduction models (6712) fnhirwa, yarnabrina

• LTSFTransformer based on cure-lab research code base (6202) geetu040

• MVTS transformer classifier (6791) geetu040

• forecasters can now support categorical X, as per tag (6704, 6732) Abhay-Lejith

• DirectReductionForecaster now has a windows_identical option (6650) hliebert

• ForecastingOptunaSearchCV can now be passed custom samplers and "higher is better" scores (6823, 6846) bastisar, gareth-brown-86, mk406

Dependency changes

• holiday (transformations soft dependency) bounds have been updated to >=0.29,<0.54

• dask (data container and parallelization back-end) bounds have been updated to <2024.8.1

Core interface changes

BaseObject and base framework

• implementers no longer need to set the package_import_alias tag when estimator dependencies have a different import name than the PEP 440 package name. All internal logic now only uses the PEP 440 package name. There is no need to remove the tag if already set, but it is no longer required.

• estimators now have a tag capability:categorical_in_X: bool to indicate that the estimator can handle categorical features in the input data X. Such estimator can be used with categorical and string-valued features if X is passed in one of the pandas based mtypes.

• the html representation of all objects now includes a link to the documentation of the object, and is now in line with the sklearn html representation.

Enhancements

BaseObject and base framework

• [ENH] improved environment package version check (6776) fkiraly

• [ENH] Remove package import alias related internal logic and tags (6821) fkiraly

• [ENH] Adding tag for categorical support in X (6704) Abhay-Lejith

• [ENH] Adding categorical support: Raising error in yes/no case (6732) Abhay-Lejith

• [ENH] Link to docs in object's html repr (6876) mateuszkasprowicz

Data sets and data loaders

• [ENH] Data Loader for M5 dataset (6731) SaiRevanth25

Data types, checks, conversions

• [ENH] check_pdmultiindex_panel to return names of invalid object columns if there are any (6797) SaiRevanth25

• [ENH] Allow object dtype in series (5886) yarnabrina

• [ENH] converter framework tests in datatypes to cover all types, including those requiring soft dependencies (6838) fkiraly

• [ENH] add missing feature_kind metadata fields to gluonts based data container checkers (6861) fkiraly

• [ENH] added feature_kind metadata in datatype checks (6490) Abhay-Lejith

• [ENH] Adding support for gluonts PandasDataset object (6668) shlok191

• [ENH] Added support for gluonts PandasDataset as a Series scitype (6837) shlok191

Forecasting

• [ENH] interface to autots ensemble (5948) MBristle

• [ENH] darts Reduction Models adapter (6712) fnhirwa, yarnabrina

• [ENH] Extension Template For Global Forecasting API (6699) XinyuWuu

• [ENH] enable multivariate data passed to autots interface (6805) fkiraly

• [ENH] Add Sampler to ForecastingOptunaSearchCV (6823) bastisar

• [ENH] Improve TestAllGlobalForecasters (6845) XinyuWuu

• [ENH] Add scoring direction to ForecastingOptunaSearchCV (6846) gareth-brown-86, mk406

• [ENH] de-novo implementation of LTSFTransformer based on cure-lab research code base (6202) geetu040

• [ENH] Add windows_identical to DirectReductionForecaster (6650) hliebert

• [ENH] updates type inference in make_reduction to use central scitype inference and allow proba tabular regressors (6893) fkiraly

• [ENH] DeepAR and NHiTS and refinements for pytorch-forecasting interface (6551) XinyuWuu

• [ENH] Interface to TinyTimeMixer foundation model (6712) geetu040

• [ENH] remove now superfluous try-excepts in forecasting API test suite (6906) fkiraly

• [ENH] improve test_global_forecasting_tag (6929) geetu040

Registry and search

• [ENH] in estimator html repr, make version retrieval safer and more flexible (6923) fkiraly

Time series anomalies, changepoints, segmentation

• [ENH] time series annotation (outliers, changepoints) - test class and full check_estimator integration (6843) fkiraly

• [ENH] Add Windowed Local Outlier Factor Anomaly Detector (6524) Alex-JG3

• [ENH] Add binary segmentation annotator for change point detection (6723) Alex-JG3

Time series classification

• [ENH] Pytorch Classifier intermediate base class for TSC (6791) geetu040

• [ENH] MVTS transformer classifier (6791) geetu040

Transformations

• [ENH] add second test params dict to Aggregator (6759) fr1ll

• [ENH] pandas inner type and global pooling for TabularToSeriesAdaptor (6752) fkiraly

• [ENH] alternative returns for VmdTransformer - mode spectra and central frequencies (6857) fkiraly

• [ENH] simplify dictionaries and alias handling in Catch22 (6104) fkiraly

• [ENH] making self._is_vectorized access more defensive in BaseTransformer (6863) fkiraly

Test framework

• [ENH] make pyproject.toml parsing for differential testing more robust against non-package relevant changes (6882) fkiraly

Vendor and onboard libraries

• [ENH] Vendor fracdiff library (6777) DinoBektesevic

• [ENH] improvements to vendored fracdiff library (6912) fkiraly

Documentation

• [DOC] Notebook and Template For Global Forecasting API (6699) XinyuWuu

• [DOC] Add authorship credits to MatrixProfileTransformer for Stumpy authors (6762) alexander-lakocy

• [DOC] add examples to StatsForecastGARCH and StatsForecastARCH docstrings (6761) melinny

• [DOC] Add alignment notebook example (6768) alexander-lakocy

• [DOC] fix transformers type table in API reference in accordance with sphinx guidelines (6771) alexander-lakocy

• [DOC] Modify editable install to make cross-platform (6758) fr1ll

• [DOC] TruncationTransformer docstring example (6765) ceroper

• [DOC] De-duplicate User Guide and Examples (closes #6767) (6770) alexander-lakocy

• [DOC] improved docstring of DWTTransformer (6764) Mitchjkjkjk

• [DOC] various improvements to user journey on documentation page (6760) fkiraly

• [DOC] Time series k means max iter parameter docstring (6726) AlexeyOm

• [DOC] cross-reference estimator search from tags API reference (6816) fkiraly, yarnabrina

• [DOC] updated docstring for check_is_mtype to match skpro check_is_mtype function (6835) julian-fong

• [DOC] example & tutorial notebooks: normalize execution counts, indentation, execute all cells (6847) fkiraly

• [DOC] clarify column handling in docstring of FourierFeatures (6834) fkiraly

• [DOC] added fork usage recommendations (6827) yarnabrina

• [DOC] change links in documentation to refer to same version (6841) yarnabrina

• [DOC] minor improvements to check_scoring docstring (6877) fkiraly

• [DOC] add proper author credits to 1:1 interface classes - aligners, distances, forecasters, parameter estimators (6850) fkiraly

• [DOC] fix docstring formatting of evaluate (6864) fkiraly

• [DOC] Add documentation for benchmarking module (6792) benHeid

• [DOC] add elections link on landing page (6910) fkiraly

• [DOC] Add example notebook for the graphical pipeline (5175) benHeid

• [DOC] git workflow guide - chained branches, fixing header fonts (6913) fkiraly

Maintenance

• [MNT] Remove tbats python version constraint (6769) fr1ll

• [MNT] Update Callable import from typing to collections.abc (6798) yarnabrina

• [MNT] Fix spellings using codespell and typos (6799) yarnabrina

• [MNT] improved environment package version check (6776) fkiraly

• [MNT] downgrade pykan version to <0.2.2 (6853) geetu040

• [MNT] add non-unicode characters check to the linter (6807) fnhirwa

• [MNT] updates and fixes to type hints (6743) ZhipengXue97

• [MNT] Resolve the issue with diacritics failing to be decoded on Windows (6862) fnhirwa

• [MNT] sync docstring and code formatting of dependency checker module with skbase (6873) fkiraly

• [MNT] Remove package import alias related internal logic and tags (6821) fkiraly

• [MNT] restrict failing Mr-SEQL version (6879) fkiraly

• [MNT] release workflow: Upgrade deprecated pypa action parameter (6878) szepeviktor

• [MNT] Fix pykan import and dependency checks (6881) fkiraly

• [MNT] temporarily pin matplotlib below 3.9.1 (6890) yarnabrina

• [MNT] make pyproject.toml parsing for differential testing more robust against non-package relevant changes (6882) fkiraly

• [MNT] formatter for jupyter notebook json in build tools (6849) fkiraly

• [MNT] sync differential testing utilities with skpro (6840) fkiraly

• [MNT] Handle deprecations from pandas (6855) fkiraly

• [MNT] sync docstring and code formatting of dependency checker module with skbase (6873) fkiraly

• [MNT] fix .all-contributorsrc syntax (6918) fkiraly

• [MNT] Resolve the issue with diacritics failing to be decoded on Windows (6862) fnhirwa

• [MNT] changelog utility: fix termination condition to retrieve merged PR (6920) fkiraly

• [MNT] restore holidays lower bound to 0.29 (6921) fkiraly

• [MNT] Updating the GHA dependencies to install OSX dependencies and setting the compiler flags (6926) fnhirwa

• [MNT] revert an erroneous instance of pandas deprecation fix (6925) fkiraly

• [MNT] Update the path to script to fix #6926 (6933) fnhirwa

• [MNT] [Dependabot](deps): Update pytest requirement from <8.3,>=7.4 to >=7.4,<8.4 (6819) dependabot[bot]

• [MNT] [Dependabot](deps): Update dask requirement from <2024.6.3 to <2024.7.2 (6818) dependabot[bot]

• [MNT] [Dependabot](deps): Update sphinx-gallery requirement from <0.17.0 to <0.18.0 (6820) dependabot[bot]

• [MNT] [Dependabot](deps): Update holidays requirement from <0.53,>=0.52 to >=0.52,<0.54 (6780) dependabot[bot]

• [MNT] [Dependabot](deps): Update sphinx requirement from !=7.2.0,<8.0.0 to !=7.2.0,<9.0.0 (6865) dependabot[bot]

• [MNT] [Dependabot](deps): Update holidays requirement from <0.54,>=0.52 to >=0.52,<0.55 (6898) dependabot[bot]

• [MNT] [Dependabot](deps): Update dask requirement from <2024.7.2 to <2024.8.1 (6907) dependabot[bot]

Fixes

BaseObject and base framework

• [BUG] fix _check_soft_dependencies for post and pre versions of patch versions (6909) fkiraly

Data types, checks, conversions

• [BUG] fix type inconsistency in conversion pandas to xarray based Series (6856) fkiraly

Forecasting

• [BUG] Fix pykan dependency and set lower bound (6789) benHeid

• [BUG] correct dependency tag for pytorch-forecasting forecasters: rename pytorch_forecasting to correct package name pytorch-forecasting (6830) XinyuWuu

Registry and search

• [BUG] fix polymorphic estimators missing in estimator overview, e.g., pytorch-forecasting forecasters (6803) fkiraly

Time series anomalies, changepoints, segmentation

• [BUG] Fix bug when predicting segments from clasp change point annotator (6756) Alex-JG3

Transformations

• [BUG] Refactor ADICVTransformer and fix CV calculation (6757) sbhobbes

• [BUG] fix BaseTransformer broadcasting condition in inverse_transform for decomposers (6824) fkiraly

• [BUG] fix MSTL inverse transform and use in forecasting pipeline (6825) fkiraly

• [BUG] fix handling of numpy integers in refactored Catch22 transformation (6934) fkiraly

Visualization

• [BUG] In plot_series, trim unused levels when verifying dataframe formatting (6754) SultanOrazbayev

Contributors

Abhay-Lejith, Alex-JG3, alexander-lakocy, AlexeyOm, bastisar, benHeid, ceroper, DinoBektesevic, fkiraly, fnhirwa, fr1ll, gareth-brown-86, geetu040, hliebert, julian-fong, mateuszkasprowicz, MBristle, melinny, Mitchjkjkjk, mk406, SaiRevanth25, sbhobbes, shlok191, SultanOrazbayev, szepeviktor, XinyuWuu, yarnabrina, ZhipengXue97

Maintenance release:

scheduled deprecations and change actions

numpy 2 compatibility

code style and pre-commit updates, using ruff for linting

For last non-maintenance content updates, see 0.30.2.

Dependency changes

numpy (core dependency) bounds have been updated to <2.1,>=1.21

skpro (soft dependency) bounds have been updated to >=2,<2.5.0

Deprecations and removals

Time series anomalies, changepoints, segmentation

The fmt argument in time series annotators is now deprecated. Users should use the predict and transform methods instead, predict instead of fmt="sparse" , and transform instead of fmt="dense" .

Time series classification

The convert_y_to_keras method in deep learning classifiers has been removed. Users who have been using this method should instead use OneHotEncoder from sklearn directly, as convert_y_to_keras is a simple wrapper around OneHotEncoder with default settings.

Contents

[MNT] raise numpy bound to numpy < 2.1 , numpy 2 compatibility ( #6624 ) @fkiraly

[MNT] Dependabot: Update skpro requirement from <2.4.0,>=2 to >=2,<2.5.0 ( #6663 ) @dependabot[bot]

[MNT] bound prophet based forecasters to numpy<2 due to incompatibility of prophet ( #6721 ) @fkiraly

[MNT] further numpy 2 compatibility fixes in estimators ( #6729 ) @fkiraly

[MNT] handle numpy 2 incompatible soft deps ( #6728 ) @fkiraly

[MNT] Upgrade code style beyond python 3.8 ( #6330 ) @yarnabrina

[MNT] Update pre commit hooks post dropping python 3.8 support ( #6331 ) @yarnabrina

[MNT] suppress aggressive freq related warnings from pandas 2.2 ( #6733 ) @fkiraly

[MNT] 0.31.0 deprecations and change actions ( #6716 ) @fkiraly

[MNT] switch to ruff as linting tool ( #6676 ) @fnhirwa

[ENH] refactor and bugfixes for environment checker utilities ( #6719 ) @fkiraly

Contributors

@fkiraly , @fnhirwa , @yarnabrina

Maintenance release:

• scheduled deprecations and change actions

• numpy 2 compatibility

• code style and pre-commit updates, using ruff for linting

For last non-maintenance content updates, see 0.30.2.

Dependency changes

• numpy (core dependency) bounds have been updated to <2.1,>=1.21

• skpro (soft dependency) bounds have been updated to >=2,<2.5.0

Deprecations and removals

Time series anomalies, changepoints, segmentation

• The fmt argument in time series annotators is now deprecated. Users should use the predict and transform methods instead, predict instead of fmt="sparse", and transform instead of fmt="dense".

Time series classification

• The convert_y_to_keras method in deep learning classifiers has been removed. Users who have been using this method should instead use OneHotEncoder from sklearn directly, as convert_y_to_keras is a simple wrapper around OneHotEncoder with default settings.

Contents

• [MNT] raise numpy bound to numpy < 2.1, numpy 2 compatibility (6624) fkiraly

• [MNT] [Dependabot](deps): Update skpro requirement from <2.4.0,>=2 to >=2,<2.5.0 (6663) dependabot[bot]

• [MNT] bound prophet based forecasters to numpy<2 due to incompatibility of prophet (6721) fkiraly

• [MNT] further numpy 2 compatibility fixes in estimators (6729) fkiraly

• [MNT] handle numpy 2 incompatible soft deps (6728) fkiraly

• [MNT] Upgrade code style beyond python 3.8 (6330) yarnabrina

• [MNT] Update pre commit hooks post dropping python 3.8 support (6331) yarnabrina

• [MNT] suppress aggressive freq related warnings from pandas 2.2 (6733) fkiraly

• [MNT] 0.31.0 deprecations and change actions (6716) fkiraly

• [MNT] switch to ruff as linting tool (6676) fnhirwa

• [ENH] refactor and bugfixes for environment checker utilities (6719) fkiraly

Contributors

fkiraly, fnhirwa, yarnabrina

Highlights

new estimator overview table and estimator search page ( #6147 ) @duydl

HFTransformersForecaster (hugging face transformers connector) now has a user friendly interface for applying PEFT methods ( #6457 ) @geetu040

ForecastingOptunaSearchCV for hyper-parameter tuning of forecasters via optuna ( #6630 ) @mk406 , @gareth-brown-86

prophetverse package forecasters are now indexed by sktime ( #6614 ) @felipeangelimvieira

pytorch-forecasting adapter, experimental global forecasting API ( #6228 ) @XinyuWuu

skforecast adapter for reduction strategies ( #6531 ) @Abhay-Lejith , @yarnabrina

EnbPI based forecaster with components from aws-fortuna ( #6449 ) @benHeid

DTW distances and aligners from dtaidistance ( #6578 ) @fkiraly

parametrize_with_checks utility for granular API compliance test setup in 2nd/3rd party libraries ( #6588 ) @fkiraly

Dependency changes

holidays (transformations soft dependency) bounds have been updated to >=0.29,<0.53

dask (data container and parallelization back-end) bounds have been updated to <2024.5.3

optuna is now a soft dependency, via the ForecastingOptunaSearchCV estimator, in the all_extras soft dependency set, with bounds <3.7

pytorch-forecasting is now a soft dependency, in the dl (deep learning) soft dependency set

skforecast is now a soft dependency, in the all_extras soft dependency set and the forecasting soft dependency set, with bounds <0.13,>=0.12.1

dtaidistance is now a soft dependency, in the all_extras soft dependency set and the alignment soft dependency set, with bounds <2.4

Core interface changes

Forecasting

The base forecaster interface now has a dedicated interface point for global forecasting or fine-tuning: in forecasters supporting global forecast, an y argument may be passed in predict , indicating new time series instances for a global forecast, or a context for foundation models. Forecasters capable of global forecasting or fine-tuning (this is the same interface point) are tagged with the tag capability:global_forecasting , value True .

The global forecasting and fine-tuning interfaces are currently experimental, and may undergo changes.

Users are invited to give feedback, and test the feature with the new pytorch-forecasting adapter.

Test framework

2nd and 3rd party extension packages can now use the parametrize_with_checks utility to set up granular API compliance tests. For detailed usage notes, consult the extender guide: Implementing Estimators .

various quality-of-life improvements have been made to facilitate indexing an estimator in the estimator overview and estimator search for developers of API compatible 2nd and 3rd party packages, without adding it directly to the main sktime repository. For detailed usage notes, consult the extender guide: Implementing Estimators , or inspect the Prophetverse forecaster as a worked example.

Enhancements

BaseObject and base framework

[ENH] prevent imports caused by _check_soft_dependencies , speed up dependency check and test collection time ( #6355 ) @fkiraly , @yarnabrina

Benchmarking, Metrics, Splitters

[ENH] Parallelization option for ForecastingBenchmark ( #6568 ) @benHeid

Data types, checks, conversions

[ENH] Added GluonTS datasets as sktime mtypes ( #6530 ) @shlok191

Distances, kernels

[ENH] DTW distances from dtaidistance ( #6578 ) @fkiraly

Forecasting

[ENH] pytorch-forecasting adapter with Global Forecasting API ( #6228 ) @XinyuWuu

[ENH] fitted parameter forwarding utility, forward statsforecast estimators’ fitted parameters ( #6349 ) @fkiraly

[ENH] EnbPI based forecaster with components from aws-fortuna ( #6449 ) @benHeid

[ENH] skforecast ForecasterAutoreg adapter ( #6531 ) @Abhay-Lejith , @yarnabrina

[ENH] Extend HFTransformersForecaster for PEFT methods ( #6457 ) @geetu040

[ENH] in BaseForecaster , move check for capability:insample to _check_fh boilerplate ( #6593 ) @XinyuWuu

[ENH] indexing prophetverse forecaster ( #6614 ) @fkiraly

[ENH] ForecastingOptunaSearchCV for hyper-parameter tuning of forecasters via optuna ( #6630 ) @mk406 , @gareth-brown-86

Registry and search

[ENH] enhanced estimator overview table - tag display and search ( #6147 ) @duydl , @fkiraly

Time series alignment

[ENH] DTW aligners from dtaidistance ( #6578 ) @fkiraly

Time series classification

[ENH] resolve duplication in KNeighborsClassifier and KNeighborsRegressor ( #6504 ) @Z-Fran

[ENH] added two test params sets to FCNNetwork ( #6562 ) @TheoWeih

[ENH] further refactor of knn classifier and regressor ( #6615 ) @fkiraly

[ENH] update tests._config to skip various sporadically failing tests for Proximity Forest and Proximity Tree until fixed ( #6638 ) @julian-fong

Time series regression

[ENH] Time Series Regression grid search ( #6118 ) @ksharma6

[ENH] test parameters for RocketRegressor ( #6149 ) @iaryangoyal

[ENH] resolve duplication in KNeighborsClassifier and KNeighborsRegressor ( #6504 ) @Z-Fran

[ENH] further refactor of knn classifier and regressor ( #6615 ) @fkiraly

Transformations

[ENH] refactor WindowSummarizer tests ( #6564 ) @fkiraly

Test framework

[ENH] differential testing for base functionality in various modules ( #6534 ) @fkiraly

[ENH] further differential testing for the transformations module ( #6533 ) @fkiraly

[ENH] differential testing in dist_kernels and clustering modules ( #6543 ) @fkiraly

[ENH] simplify and add differential testing to forecasting.compose.tests module ( #6563 ) @fkiraly

[ENH] simplify and add differential testing to sktime.pipeline module ( #6565 ) @fkiraly

[ENH] differential testing in benchmarking module ( #6566 ) @fkiraly

[ENH] move doctests to main test suite to ensure conditional execution ( #6536 ) @fkiraly

[ENH] minor improvements to test efficiency ( #6586 ) @fkiraly

[ENH] parametrize_with_checks utility for granular API compliance test setup in 2nd/3rd party libraries ( #6588 ) @fkiraly

[ENH] differential testing to utils module ( #6620 ) @fkiraly

[ENH] differential testing and minor improvements to forecasting.base tests ( #6619 ) @fkiraly

[ENH] differential testing for performance_metrics module ( #6616 ) @fkiraly

[ENH] fixes and improvements to pytest doctest integration ( #6621 ) @fkiraly

Documentation

[DOC] fix broken links on webpage docs ( #6339 ) @duydl

[DOC] document more tags ( #6496 ) @fkiraly

[DOC] fix minor typos in tags API reference ( #6631 ) @fkiraly

[DOC] update dependencies reference ( #6655 ) @emmanuel-ferdman

[DOC] fix minor typo in developer comment in BaseTransformer ( #6689 ) @Spinachboul

[DOC] rst roadmap documentation page stale since 2021 - replace by correct links to recent roadmaps ( #6556 ) @fkiraly

[DOC] clarify docs on ARIMA estimators, add author credits for upstream ( #6705 ) @fkiraly

[DOC] credit @doberbauer` for pykalman python 3.11 compatibility fix ( #6662 ) @doberbauer

Maintenance

[MNT] Dependabot: Update holidays requirement from <0.51,>=0.29 to >=0.29,<0.52 ( #6634 ) @dependabot[bot]

[MNT] Dependabot: Update holidays requirement from <0.52,>=0.29 to >=0.52,<0.53 ( #6702 ) @dependabot[bot]

[MNT] Dependabot: Update dask requirement from <2024.6.1 to <2024.6.2 ( #6643 ) @dependabot[bot]

[MNT] Dependabot: Update numba requirement from <0.60,>=0.53 to >=0.53,<0.61 ( #6590 ) @dependabot[bot]

[MNT] Dependabot: Update dask requirement from <2024.6.2 to <2024.6.3 ( #6647 ) @dependabot[bot]

[MNT] remove coverage reporting and pytest-cov from PR CI and setup.cfg ( #6363 ) @fkiraly

[MNT] numpy 2 compatibility fixes - estimators ( #6626 ) @fkiraly

[MNT] scipy 1.14.0 compatibility for deep_equals plugin for csr_matrix ( #6664 ) @fkiraly

[MNT] deprecate unused _check_soft_dependencies argument suppress_import_stdout ( #6691 ) @fkiraly

Fixes

Benchmarking, Metrics, Splitters

[BUG] fix AUCalibration probabilistic metric for multivariate case ( #6617 ) @fkiraly

Data loaders

[BUG] fix bug 4076: PerformanceWarning in load_from_tsfile_to_dataframe ( #6632 ) @ericjb

Data types, checks, conversions

[BUG] patch over pandas 2.2.X issue in freq timestamp/period round trip conversion for period start timestamps such as "MonthBegin" ( #6574 ) @fkiraly

Forecasting

[BUG] fix passing of y in ForecastingPipeline ( #6706 ) @fkiraly

Time series classification

[BUG] Fix bug in fitted parameter override in pyts and tslearn adapters ( #6707 ) @fkiraly

Time series clustering

[BUG] Fix bug in fitted parameter override in pyts and tslearn adapters ( #6707 ) @fkiraly

Time series regression

[BUG] in TimeSeriesForestRegressor , fix failure: self.criterion does not exist ( #6573 ) @ksharma6

Test framework

[BUG] partially revert pytest.skip change from #6233 due to side effects in downstream test suites ( #6508 ) @fkiraly

[BUG] fix test failures introduced by differential testing refactor ( #6585 ) @fkiraly

Transformations

[BUG] fix HolidayFeatures crashes if dataframe doesn’t contain specified date ( #6550 ) @fnhirwa

[BUG] in Differencer , make explicit clone to avoid SettingWithCopyWarning ( #6567 ) @benHeid

[BUG] minirocket: fix zero division errors #5174 ( #6612 ) @benshaw2

[BUG] ensure correct setting of requires_X and requires_y tag for FeatureUnion ( #6695 ) @fkiraly

[BUG] ensure correct setting of requires_X and requires_y tag for TransformerPipeline ( #6692 ) @fkiraly

[BUG] partial fix for dropped column names in PaddingTransformer ( #6693 ) @fkiraly

Contributors

@Abhay-Lejith , @benHeid , @benshaw2 , @doberbauer , @emmanuel-ferdman , @ericjb , @felipeangelimvieira , @fkiraly , @fnhirwa , @gareth-brown-86 , @geetu040 , @iaryangoyal , @julian-fong , @ksharma6 , @mk406 , @shlok191 , @Spinachboul , @TheoWeih , @XinyuWuu , @yarnabrina , @Z-Fran

Highlights

• new estimator overview table and estimator search page (6147) duydl

• HFTransformersForecaster (hugging face transformers connector) now has a user friendly interface for applying PEFT methods (6457) geetu040

• ForecastingOptunaSearchCV for hyper-parameter tuning of forecasters via optuna (6630) mk406, gareth-brown-86

• prophetverse package forecasters are now indexed by sktime (6614) felipeangelimvieira

• pytorch-forecasting adapter, experimental global forecasting API (6228) XinyuWuu

• skforecast adapter for reduction strategies (6531) Abhay-Lejith, yarnabrina

• EnbPI based forecaster with components from aws-fortuna (6449) benHeid

• DTW distances and aligners from dtaidistance (6578) fkiraly

• parametrize_with_checks utility for granular API compliance test setup in 2nd/3rd party libraries (6588) fkiraly

Dependency changes

• holidays (transformations soft dependency) bounds have been updated to >=0.29,<0.53

• dask (data container and parallelization back-end) bounds have been updated to <2024.5.3

• optuna is now a soft dependency, via the ForecastingOptunaSearchCV estimator, in the all_extras soft dependency set, with bounds <3.7

• pytorch-forecasting is now a soft dependency, in the dl (deep learning) soft dependency set

• skforecast is now a soft dependency, in the all_extras soft dependency set and the forecasting soft dependency set, with bounds <0.13,>=0.12.1

• dtaidistance is now a soft dependency, in the all_extras soft dependency set and the alignment soft dependency set, with bounds <2.4

Core interface changes

Forecasting

The base forecaster interface now has a dedicated interface point for global forecasting or fine-tuning: in forecasters supporting global forecast, an y argument may be passed in predict, indicating new time series instances for a global forecast, or a context for foundation models. Forecasters capable of global forecasting or fine-tuning (this is the same interface point) are tagged with the tag capability:global_forecasting, value True.

The global forecasting and fine-tuning interfaces are currently experimental, and may undergo changes.

Users are invited to give feedback, and test the feature with the new pytorch-forecasting adapter.

Test framework

• 2nd and 3rd party extension packages can now use the parametrize_with_checks utility to set up granular API compliance tests. For detailed usage notes, consult the extender guide: developer_guide_add_estimators.

• various quality-of-life improvements have been made to facilitate indexing an estimator in the estimator overview and estimator search for developers of API compatible 2nd and 3rd party packages, without adding it directly to the main sktime repository. For detailed usage notes, consult the extender guide: developer_guide_add_estimators, or inspect the Prophetverse forecaster as a worked example.

Enhancements

BaseObject and base framework

• [ENH] prevent imports caused by _check_soft_dependencies, speed up dependency check and test collection time (6355) fkiraly, yarnabrina

Benchmarking, Metrics, Splitters

• [ENH] Parallelization option for ForecastingBenchmark (6568) benHeid

Data types, checks, conversions

• [ENH] Added GluonTS datasets as sktime mtypes (6530) shlok191

Distances, kernels

• [ENH] DTW distances from dtaidistance (6578) fkiraly

Forecasting

• [ENH] pytorch-forecasting adapter with Global Forecasting API (6228) XinyuWuu

• [ENH] fitted parameter forwarding utility, forward statsforecast estimators' fitted parameters (6349) fkiraly

• [ENH] EnbPI based forecaster with components from aws-fortuna (6449) benHeid

• [ENH] skforecast ForecasterAutoreg adapter (6531) Abhay-Lejith, yarnabrina

• [ENH] Extend HFTransformersForecaster for PEFT methods (6457) geetu040

• [ENH] in BaseForecaster, move check for capability:insample to _check_fh boilerplate (6593) XinyuWuu

• [ENH] indexing prophetverse forecaster (6614) fkiraly

• [ENH] ForecastingOptunaSearchCV for hyper-parameter tuning of forecasters via optuna (6630) mk406, gareth-brown-86

Registry and search

• [ENH] enhanced estimator overview table - tag display and search (6147) duydl, fkiraly

Time series alignment

• [ENH] DTW aligners from dtaidistance (6578) fkiraly

Time series classification

• [ENH] resolve duplication in KNeighborsClassifier and KNeighborsRegressor (6504) Z-Fran

• [ENH] added two test params sets to FCNNetwork (6562) TheoWeih

• [ENH] further refactor of knn classifier and regressor (6615) fkiraly

• [ENH] update tests._config to skip various sporadically failing tests for Proximity Forest and Proximity Tree until fixed (6638) julian-fong

Time series regression

• [ENH] Time Series Regression grid search (6118) ksharma6

• [ENH] test parameters for RocketRegressor (6149) iaryangoyal

• [ENH] resolve duplication in KNeighborsClassifier and KNeighborsRegressor (6504) Z-Fran

• [ENH] further refactor of knn classifier and regressor (6615) fkiraly

Transformations

• [ENH] refactor WindowSummarizer tests (6564) fkiraly

Test framework

• [ENH] differential testing for base functionality in various modules (6534) fkiraly

• [ENH] further differential testing for the transformations module (6533) fkiraly

• [ENH] differential testing in dist_kernels and clustering modules (6543) fkiraly

• [ENH] simplify and add differential testing to forecasting.compose.tests module (6563) fkiraly

• [ENH] simplify and add differential testing to sktime.pipeline module (6565) fkiraly

• [ENH] differential testing in benchmarking module (6566) fkiraly

• [ENH] move doctests to main test suite to ensure conditional execution (6536) fkiraly

• [ENH] minor improvements to test efficiency (6586) fkiraly

• [ENH] parametrize_with_checks utility for granular API compliance test setup in 2nd/3rd party libraries (6588) fkiraly

• [ENH] differential testing to utils module (6620) fkiraly

• [ENH] differential testing and minor improvements to forecasting.base tests (6619) fkiraly

• [ENH] differential testing for performance_metrics module (6616) fkiraly

• [ENH] fixes and improvements to pytest doctest integration (6621) fkiraly

Documentation

• [DOC] fix broken links on webpage docs (6339) duydl

• [DOC] document more tags (6496) fkiraly

• [DOC] fix minor typos in tags API reference (6631) fkiraly

• [DOC] update dependencies reference (6655) emmanuel-ferdman

• [DOC] fix minor typo in developer comment in BaseTransformer (6689) Spinachboul

• [DOC] rst roadmap documentation page stale since 2021 - replace by correct links to recent roadmaps (6556) fkiraly

• [DOC] clarify docs on ARIMA estimators, add author credits for upstream (6705) fkiraly

• [DOC] credit doberbauer` for pykalman python 3.11 compatibility fix (6662) doberbauer

Maintenance

• [MNT] [Dependabot](deps): Update holidays requirement from <0.51,>=0.29 to >=0.29,<0.52 (6634) dependabot[bot]

• [MNT] [Dependabot](deps): Update holidays requirement from <0.52,>=0.29 to >=0.52,<0.53 (6702) dependabot[bot]

• [MNT] [Dependabot](deps): Update dask requirement from <2024.6.1 to <2024.6.2 (6643) dependabot[bot]

• [MNT] [Dependabot](deps): Update numba requirement from <0.60,>=0.53 to >=0.53,<0.61 (6590) dependabot[bot]

• [MNT] [Dependabot](deps): Update dask requirement from <2024.6.2 to <2024.6.3 (6647) dependabot[bot]

• [MNT] remove coverage reporting and pytest-cov from PR CI and setup.cfg (6363) fkiraly

• [MNT] numpy 2 compatibility fixes - estimators (6626) fkiraly

• [MNT] scipy 1.14.0 compatibility for deep_equals plugin for csr_matrix (6664) fkiraly

• [MNT] deprecate unused _check_soft_dependencies argument suppress_import_stdout (6691) fkiraly

Fixes

Benchmarking, Metrics, Splitters

• [BUG] fix AUCalibration probabilistic metric for multivariate case (6617) fkiraly

Data loaders

• [BUG] fix bug 4076: PerformanceWarning in load_from_tsfile_to_dataframe (6632) ericjb

Data types, checks, conversions

• [BUG] patch over pandas 2.2.X issue in freq timestamp/period round trip conversion for period start timestamps such as "MonthBegin" (6574) fkiraly

Forecasting

• [BUG] fix passing of y in ForecastingPipeline (6706) fkiraly

Time series classification

• [BUG] Fix bug in fitted parameter override in pyts and tslearn adapters (6707) fkiraly

Time series clustering

• [BUG] Fix bug in fitted parameter override in pyts and tslearn adapters (6707) fkiraly

Time series regression

• [BUG] in TimeSeriesForestRegressor, fix failure: self.criterion does not exist (6573) ksharma6

Test framework

• [BUG] partially revert pytest.skip change from #6233 due to side effects in downstream test suites (6508) fkiraly

• [BUG] fix test failures introduced by differential testing refactor (6585) fkiraly

Transformations

• [BUG] fix HolidayFeatures crashes if dataframe doesn't contain specified date (6550) fnhirwa

• [BUG] in Differencer, make explicit clone to avoid SettingWithCopyWarning (6567) benHeid

• [BUG] minirocket: fix zero division errors #5174 (6612) benshaw2

• [BUG] ensure correct setting of requires_X and requires_y tag for FeatureUnion (6695) fkiraly

• [BUG] ensure correct setting of requires_X and requires_y tag for TransformerPipeline (6692) fkiraly

• [BUG] partial fix for dropped column names in PaddingTransformer (6693) fkiraly

Contributors

Abhay-Lejith, benHeid, benshaw2, doberbauer, emmanuel-ferdman, ericjb, felipeangelimvieira, fkiraly, fnhirwa, gareth-brown-86, geetu040, iaryangoyal, julian-fong, ksharma6, mk406, shlok191, Spinachboul, TheoWeih, XinyuWuu, yarnabrina, Z-Fran

Minimal maintenance update with actions consolidating onboard packages.

For last major feature update, see 0.29.1.

Contents

[MNT] reorganization of onboard libs - pykalman , vmdpy ( #6535 ) @fkiraly

[MNT] differential testing for split module ( #6532 ) @fkiraly

Minimal maintenance update with actions consolidating onboard packages.

For last major feature update, see 0.29.1.

Contents

• [MNT] reorganization of onboard libs - pykalman, vmdpy (6535) fkiraly

• [MNT] differential testing for split module (6532) fkiraly

Major upgrade to the time series anomaly, changepoints, segmentation API ( @Alex-JG3 ). Users should review the section in the release notes.

Kindly also note the python 3.8 End-of-life warning below.

Also includes scheduled deprecations and change actions.

For last major feature update, see 0.29.1.

Dependency changes

joblib is now an explicit core dependency, with bounds <1.5,>=1.2.0 . Previously, joblib was an indirect core dependency, via scikit-learn . Due to direct imports, this was changed to an explicit dependency.

scikit-learn (core dependency) bounds have been updated to >=0.24,<1.6.0

scikit-base (core dependency) bounds have been updated to >=0.6.1,<0.9.0

skpro (soft dependency) bounds have been updated to >=2,<2.4.0

kotsu is not longer a soft dependency required by the forecasting benchmarking framework. The kotsu package is no longer maintained, and its necessary imports have beend moved to sktime as private utilities until refactor. See #6514 .

pykalman (transformations soft dependency) has been forked into sktime , as sktime.libs.pykalman , as the original package is no longer maintained, see sktime issue 5414 or pykalman issue 109.

The package fork will be maintained in sktime .

Direct users of pykalman can replace imports from pykalman import x with equivalent imports from sktime.libs.pykalman import x .

Indirect users via the transformer KalmanFilterTransformerPK will not be impacted as APIs do not change, except that they no longer require the original pykalman package in their python environment.

Core interface changes

The time series annotation, anomalies, changepoints, segmentation API has been fully reworked to be in line with scikit-base patterns, sktime tags, and to provide a more consistent and flexible interface.

the API provides predict methods for annotation labels, e.g., segments, outlier points, and a transform method for indicator series, for instance 1/0 indicator whether an anomaly is present at the time stamp.

the fmt argument used in some estimators is now deprecated, in favour of using predict or transform .

The type of annotation, e.g., change points or segmentation, is encoded by the new tag task used in time series annotators, with values anomaly_detection , segmentation , changepoint_detection .

Low-level methods allow polymorphic use of annotators, e.g., a changepoint detector to be used for segmentation, via predict_points or predict_segments . The predict method defaults to the type of annotation defined by task .

A full tutorial with examples will be created over the next release cycles, and further enhancements are planned.

Deprecations and removals

Python 3.8 End-of-life

sktime now requires Python version >=3.9 . No errors will be raised on Python 3.8, but test coverage and support for Python 3.8 has been dropped.

Kindly note for context: python 3.8 will reach end of life in October 2024, and multiple sktime core dependencies, including scikit-learn , have already dropped support for 3.8.

Forecasting

cINNForecaster has been renamed to CINNForecaster . The estimator is no longer available under its old name, after the deprecation period. Users should replace any imports of cINNForecaster with imports of CINNForecaster .

Enhancements

[ENH] Rework of base series annotator API ( #6265 ) @Alex-JG3

[ENH] upgrade is_module_changed test utility for paths ( #6518 ) @fkiraly

Documentation

[DOC] updated all_estimators docstring for re.Pattern support ( #6478 ) @fkiraly

Maintenance

[MNT] Dependabot: Update skpro requirement from <2.3.0,>=2 to >=2,<2.4.0 ( #6443 ) @dependabot[bot]

[MNT] Dependabot: Update scikit-learn requirement from <1.5.0,>=0.24 to >=0.24,<1.6.0 ( #6462 ) @dependabot[bot]

[MNT] Dependabot: Update scikit-base requirement from <0.8.0,>=0.6.1 to >=0.6.1,<0.9.0 ( #6488 ) @dependabot[bot]

[MNT] drop test coverage on python 3.8 in CI ( #6329 ) @yarnabrina

[MNT] final change cycle (0.30.0) for renaming cINNForecaster to CINNForecaster ( #6367 ) @geetu040

[MNT] added joblib as core dependency ( #6384 ) @yarnabrina

[MNT] 0.30.0 deprecations and change actions ( #6468 ) @fkiraly

[MNT] modified CRLF line endings to LF line endings ( #6512 ) @yarnabrina

[MNT] Move dependency checkers to separate module in utils ( #6354 ) @fkiraly

[MNT] resolution to pykalman issue - sktime local pykalman fork ( #6188 ) @fkiraly

[MNT] add systematic differential test switch to low-level tests ( #6511 ) @fkiraly

[MNT] isolate utils module init and sktime init from external imports ( #6516 ) @fkiraly

[MNT] preparing refactor of benchmark framework: folding minimal kotsu library into sktime ( #6514 ) @fkiraly

[MNT] run tests in distances module only if it has changed ( #6517 ) @fkiraly

[MNT] refactor pykalman tests to pytest and conditional execution ( #6519 ) @fkiraly

[MNT] conditional execution of tests in datatypes module ( #6520 ) @fkiraly

Contributors

@Alex-JG3 , @dependabot[bot] , @fkiraly , @geetu040 , @yarnabrina

Major upgrade to the time series anomaly, changepoints, segmentation API (Alex-JG3). Users should review the section in the release notes.

Kindly also note the python 3.8 End-of-life warning below.

Also includes scheduled deprecations and change actions.

For last major feature update, see 0.29.1.

Dependency changes

• joblib is now an explicit core dependency, with bounds <1.5,>=1.2.0. Previously, joblib was an indirect core dependency, via scikit-learn. Due to direct imports, this was changed to an explicit dependency.

• scikit-learn (core dependency) bounds have been updated to >=0.24,<1.6.0

• scikit-base (core dependency) bounds have been updated to >=0.6.1,<0.9.0

• skpro (soft dependency) bounds have been updated to >=2,<2.4.0

• kotsu is not longer a soft dependency required by the forecasting benchmarking framework. The kotsu package is no longer maintained, and its necessary imports have beend moved to sktime as private utilities until refactor. See 6514.

• pykalman (transformations soft dependency) has been forked into sktime, as sktime.libs.pykalman, as the original package is no longer maintained, see sktime issue 5414 or pykalman issue 109.

  • The package fork will be maintained in sktime.

  • Direct users of pykalman can replace imports from pykalman import x with equivalent imports from sktime.libs.pykalman import x.

  • Indirect users via the transformer KalmanFilterTransformerPK will not be impacted as APIs do not change, except that they no longer require the original pykalman package in their python environment.

Core interface changes

The time series annotation, anomalies, changepoints, segmentation API has been fully reworked to be in line with scikit-base patterns, sktime tags, and to provide a more consistent and flexible interface.

• the API provides predict methods for annotation labels, e.g., segments, outlier points, and a transform method for indicator series, for instance 1/0 indicator whether an anomaly is present at the time stamp.

• the fmt argument used in some estimators is now deprecated, in favour of using predict or transform.

• The type of annotation, e.g., change points or segmentation, is encoded by the new tag task used in time series annotators, with values anomaly_detection, segmentation, changepoint_detection.

• Low-level methods allow polymorphic use of annotators, e.g., a changepoint detector to be used for segmentation, via predict_points or predict_segments. The predict method defaults to the type of annotation defined by task.

A full tutorial with examples will be created over the next release cycles, and further enhancements are planned.

Deprecations and removals

Python 3.8 End-of-life

sktime now requires Python version >=3.9. No errors will be raised on Python 3.8, but test coverage and support for Python 3.8 has been dropped.

Kindly note for context: python 3.8 will reach end of life in October 2024, and multiple sktime core dependencies, including scikit-learn, have already dropped support for 3.8.

Forecasting

cINNForecaster has been renamed to CINNForecaster. The estimator is no longer available under its old name, after the deprecation period. Users should replace any imports of cINNForecaster with imports of CINNForecaster.

Enhancements

• [ENH] Rework of base series annotator API (6265) Alex-JG3

• [ENH] upgrade is_module_changed test utility for paths (6518) fkiraly

Documentation

• [DOC] updated all_estimators docstring for re.Pattern support (6478) fkiraly

Maintenance

• [MNT] [Dependabot](deps): Update skpro requirement from <2.3.0,>=2 to >=2,<2.4.0 (6443) dependabot[bot]

• [MNT] [Dependabot](deps): Update scikit-learn requirement from <1.5.0,>=0.24 to >=0.24,<1.6.0 (6462) dependabot[bot]

• [MNT] [Dependabot](deps): Update scikit-base requirement from <0.8.0,>=0.6.1 to >=0.6.1,<0.9.0 (6488) dependabot[bot]

• [MNT] drop test coverage on python 3.8 in CI (6329) yarnabrina

• [MNT] final change cycle (0.30.0) for renaming cINNForecaster to CINNForecaster (6367) geetu040

• [MNT] added joblib as core dependency (6384) yarnabrina

• [MNT] 0.30.0 deprecations and change actions (6468) fkiraly

• [MNT] modified CRLF line endings to LF line endings (6512) yarnabrina

• [MNT] Move dependency checkers to separate module in utils (6354) fkiraly

• [MNT] resolution to pykalman issue - sktime local pykalman fork (6188) fkiraly

• [MNT] add systematic differential test switch to low-level tests (6511) fkiraly

• [MNT] isolate utils module init and sktime init from external imports (6516) fkiraly

• [MNT] preparing refactor of benchmark framework: folding minimal kotsu library into sktime (6514) fkiraly

• [MNT] run tests in distances module only if it has changed (6517) fkiraly

• [MNT] refactor pykalman tests to pytest and conditional execution (6519) fkiraly

• [MNT] conditional execution of tests in datatypes module (6520) fkiraly

Contributors

Alex-JG3, dependabot[bot], fkiraly, geetu040, yarnabrina

Highlights

TransformSelectForecaster to apply different forecasters depending on series type (e.g., intermittent, lumpy) ( #6453 ) @shlok191

Kolmogorov-Arnold Network (KAN) forecaster ( #6386 ) @benHeid

New probabilistic forecast metrics: interval width (sharpness), area under the calibration curve ( #6437 , #6460 ) @fkiraly

Data loader for fpp3 (Forecasting, Princniples and Practice) datasets via rdata package, in sktime data formats ( #6477 ) @ericjb

Bollinger Bands transformation ( #6473 ) @ishanpai

ADI/CV2 (Syntetos/Boylan) feature extractor ( #6336 ) @shlok191

ExpandingCutoffSplitter - splitter by moving cutoff ( #6360 ) @ninedigits

Dependency changes

holidays (transformations soft dependency) bounds have been updated to >=0.29,<0.50

pycatch22 (transformations soft dependency) bounds have been updated to <0.4.6

dtw-python (distances and alignment soft dependency) bounds have been updated to >=1.3,<1.6

dask (data container and parallelization back-end) bounds have been updated to <2024.5.2

transformers (forecasting soft dependency) bounds have been updated to <4.41.0

Core interface changes

Benchmarking, Metrics, Splitters

all metrics for point forecasts now support weighting, via the sample_weight parameter. If passed, the metric will be weighted by the sample weights. For hierarchical data, the weights are applied to the series level, in this case all series need to have same length. Probabilistic metrics do not support weighting yet, this will be added in a future release.

Time series alignment

all time series aligners now possess the capability:unequal_length tag, which is True if the aligner can handle time series of unequal length, and False otherwise. An informative error message, based on the tag, is now raised if an aligner not supporting unequal length time series is used on such data.

Deprecations and removals

Time series classification

The convert_y_to_keras method in deep learning classifiers has been deprecated and will be removed in 0.31.0. Users who have been using this method should instead use OneHotEncoder from sklearn directly, as convert_y_to_keras is a simple wrapper around OneHotEncoder with default settings.

Enhancements

BaseObject and base framework

Benchmarking, Metrics, Splitters

[ENH] ExpandingCutoffSplitter - splitter by moving cutoff ( #6360 ) @ninedigits

[ENH] Interval width (sharpness) metric ( #6437 ) @fkiraly

[ENH] unsigned area under the calibration curve metric for distribution forecasts ( #6460 ) @fkiraly

[ENH] forecasting metrics: ensure uniform support and testing for sample_weight parameter ( #6495 ) @fkiraly

Data loaders

[ENH] data loader for fpp3 datasets from CRAN via rdata package, to sktime data formats ( #6477 ) @ericjb

Data types, checks, conversions

[ENH] Polars conversion utilities ( #6455 ) @pranavvp16

Forecasting

[ENH] Kolmogorov-Arnold Network (KAN) forecaster ( #6386 ) @benHeid

[ENH] Compositor to apply forecasters depending on series type (e.g., intermittent) ( #6453 ) @shlok191

[ENH] compatibility of ForecastingHorizon with pandas freq 2Y on pandas 2.2.0 and above ( #6500 ) @fkiraly

[ENH] add test case for ForecastingHorizon pandas 2.2.X compatibility, failure case #6499 ( #6503 ) @fkiraly

[ENH] remove Prophet from test_differencer_cutoff ( #6492 ) @fkiraly

[ENH] address deprecation and raise error in test_differencer_cutoff ( #6493 ) @fkiraly

Time series alignment

[ENH] time series aligners capability check at input, tag for unequal length capability ( #6486 ) @fkiraly

Time series classification

[ENH] Make deep classifier’s convert_y_to_keras private ( #6373 ) @cedricdonie

[ENH] classification test scenario with three classes and pd-multiindex mtype ( #6374 ) @fkiraly

[ENH] test classifiers on str dtype y , ensure predict returns same type and labels ( #6428 ) @fkiraly

Transformations

[ENH] Test Parameters for FinancialHolidaysTransformer ( #6334 ) @sharma-kshitij-ks

[ENH] ADI/CV feature extractor ( #6336 ) @shlok191

[ENH] Bollinger Bands ( #6473 ) @ishanpai

Test framework

[ENH] enable check_estimator and QuickTester.run_tests to work with skip marked pytest tests ( #6233 ) @YelenaYY

[ENH] make get_packages_with_changed_specs safe to mutation of return ( #6451 ) @fkiraly

Visualization

[ENH] plot_series improved to use matplotlib conventions; plot_interval can now plot multiple overlaid intervals ( #6416 , #6501 ) @ericjb

Documentation

[DOC] remove redundant/duplicative classification tutorial notebooks ( #6401 ) @fkiraly

[DOC] update meetup time to new 1pm slot ( #6402 ) @fkiraly

[DOC] explanation of get_test_params in test framework example ( #6434 ) @fkiraly

[DOC] fix download badges in README ( #6479 ) @fkiraly

[DOC] improved formatting of transformation docstrings ( #6489 ) @fkiraly

[DOC] document more tags: transformations ( #6351 ) @fkiraly

[DOC] Improve docstrings for metrics ( #6419 ) @fkiraly

[DOC] fixed wrong sentence in the documentation ( #6375 ) @helloplayer1

[DOC] Correct docstring for conversion functions of dask_to_pd ( #6439 ) @pranavvp16

[DOC] Fix hugging face transformers documentation ( #6450` ) @benheid

[DOC] plot_calibration docstring - formal explanation of the plot ( #6414 ) @fkiraly

[DOC] high-level explanation of deprecation policy principles ( #6464 ) @fkiraly

Maintenance

[MNT] Dependabot: Update holidays requirement from <0.49,>=0.29 to >=0.29,<0.50 ( #6456 ) @dependabot[bot]

[MNT] Dependabot: Update pycatch22 requirement from <0.4.4 to <0.4.6`` ( #6442 ) @dependabot[bot]

[MNT] Dependabot: Update sphinx-design requirement from <0.6.0 to <0.7.0 ( #6471 ) @dependabot[bot]

[MNT] Dependabot: Update dask requirement from <2024.5.1 to <2024.5.2 ( #6444 ) @dependabot[bot]

[MNT] Dependabot: Update dtw-python requirement from <1.5,>=1.3 to >=1.3,<1.6 ( #6474 ) @dependabot[bot]

[MNT] include unit tests in sktime/tests in per module tests ( #6353 ) @yarnabrina

[MNT] maintenance changes for AutoTBATS ( #6400 ) @yarnabrina

[MNT] bound transformers<4.41.0 ( #6447 ) @fkiraly

[MNT] sklearn 1.5.0 compatibility patch ( #6464 ) @fkiraly

[MNT] skip doctest for all_estimators ( #6476 ) @fkiraly

[MNT] address various deprecation and computation warnings ( #6482 ) @fkiraly

[MNT] address further deprecation warnings from pandas ( #6494 ) @fkiraly

[MNT] fix the docs local build failure due to corrupt notebook ( #6426 ) @fnhirwa

Fixes

Forecasting

[BUG] fix ForecastX when forecaster_X_exogeneous="complement" ( #6433 ) @fnhirwa

[BUG] Modified VAR code to allow predict_quantiles of 0.5 (fixes #4742) ( #6441 ) @meraldoantonio

Neural networks

[BUG] Remove duplicated BaseDeepNetworkPyTorch in networks.base ( #6398 ) @luca-miniati

Time series classification

[BUG] Resolve LSTMFCNClassifier changing callback parameter ( #6239 ) @ArthrowAbstract

[BUG] fix _get_train_probs in some classifiers to accept any input data type ( #6377 ) @fkiraly

[BUG] fix BaggingClassifier for column subsampling case ( #6429 ) @fkiraly

[BUG] fix ProximityForest , tree, stump, and IndividualBOSS returning y of different type in predict ( #6432 ) @fkiraly

[BUG] fix classifier default _predict returning integer labels always, even if fit y was not integer ( #6430 ) @fkiraly

[BUG] in CNNClassifier , ensure filter_sizes and padding is passed on ( #6452 ) @fkiraly

[BUG] fix BaseClassifier.fit_predict and fit_predict_proba for pd-multiindex mtype ( #6491 ) @fkiraly

Time series regression

[BUG] Resolve LSTMFCNRegressor changing callback parameter ( #6239 ) @ArthrowAbstract

[BUG] in CNNRegressor , ensure filter_sizes and padding is passed on ( #6452 ) @fkiraly

Transformations

[BUG] fix to make LabelEncoder compatible with sktime pipelines ( #6458 ) @Abhay-Lejith

Test framework

[BUG] allow metric classes to be called with multilevel arg if series is not hierarchical ( #6418 ) @fkiraly

[BUG] fix test_run_test_for_class logic check if ONLY_CHANGED_MODULES flag is False and all estimator dependencies are present ( #6383 ) @fkiraly

[BUG] fix test_run_test_for_class test logic ( #6448 ) @fkiraly

Visualization

[BUG] fix xticks fore date-like data in plot_series ( #6416 , #6501 ) @ericjb

Contributors

@Abhay-Lejith , @ArthrowAbstract , @benHeid , @cedricdonie , @ericjb , @fkiraly , @fnhirwa , @helloplayer1 , @ishanpai , @luca-miniati , @meraldoantonio , @ninedigits , @pranavvp16 , @sharma-kshitij-ks , @shlok191 , @yarnabrina , @YelenaYY

Highlights

• TransformSelectForecaster to apply different forecasters depending on series type (e.g., intermittent, lumpy) (6453) shlok191

• Kolmogorov-Arnold Network (KAN) forecaster (6386) benHeid

• New probabilistic forecast metrics: interval width (sharpness), area under the calibration curve (6437, 6460) fkiraly

• Data loader for fpp3 (Forecasting, Princniples and Practice) datasets via rdata package, in sktime data formats (6477) ericjb

• Bollinger Bands transformation (6473) ishanpai

• ADI/CV2 (Syntetos/Boylan) feature extractor (6336) shlok191

• ExpandingCutoffSplitter - splitter by moving cutoff (6360) ninedigits

Dependency changes

• holidays (transformations soft dependency) bounds have been updated to >=0.29,<0.50

• pycatch22 (transformations soft dependency) bounds have been updated to <0.4.6

• dtw-python (distances and alignment soft dependency) bounds have been updated to >=1.3,<1.6

• dask (data container and parallelization back-end) bounds have been updated to <2024.5.2

• transformers (forecasting soft dependency) bounds have been updated to <4.41.0

Core interface changes

Benchmarking, Metrics, Splitters

• all metrics for point forecasts now support weighting, via the sample_weight parameter. If passed, the metric will be weighted by the sample weights. For hierarchical data, the weights are applied to the series level, in this case all series need to have same length. Probabilistic metrics do not support weighting yet, this will be added in a future release.

Time series alignment

• all time series aligners now possess the capability:unequal_length tag, which is True if the aligner can handle time series of unequal length, and False otherwise. An informative error message, based on the tag, is now raised if an aligner not supporting unequal length time series is used on such data.

Deprecations and removals

Time series classification

• The convert_y_to_keras method in deep learning classifiers has been deprecated and will be removed in 0.31.0. Users who have been using this method should instead use OneHotEncoder from sklearn directly, as convert_y_to_keras is a simple wrapper around OneHotEncoder with default settings.

Enhancements

BaseObject and base framework

Benchmarking, Metrics, Splitters

• [ENH] ExpandingCutoffSplitter - splitter by moving cutoff (6360) ninedigits

• [ENH] Interval width (sharpness) metric (6437) fkiraly

• [ENH] unsigned area under the calibration curve metric for distribution forecasts (6460) fkiraly

• [ENH] forecasting metrics: ensure uniform support and testing for sample_weight parameter (6495) fkiraly

Data loaders

• [ENH] data loader for fpp3 datasets from CRAN via rdata package, to sktime data formats (6477) ericjb

Data types, checks, conversions

• [ENH] Polars conversion utilities (6455) pranavvp16

Forecasting

• [ENH] Kolmogorov-Arnold Network (KAN) forecaster (6386) benHeid

• [ENH] Compositor to apply forecasters depending on series type (e.g., intermittent) (6453) shlok191

• [ENH] compatibility of ForecastingHorizon with pandas freq 2Y on pandas 2.2.0 and above (6500) fkiraly

• [ENH] add test case for ForecastingHorizon pandas 2.2.X compatibility, failure case #6499 (6503) fkiraly

• [ENH] remove Prophet from test_differencer_cutoff (6492) fkiraly

• [ENH] address deprecation and raise error in test_differencer_cutoff (6493) fkiraly

Time series alignment

• [ENH] time series aligners capability check at input, tag for unequal length capability (6486) fkiraly

Time series classification

• [ENH] Make deep classifier's convert_y_to_keras private (6373) cedricdonie

• [ENH] classification test scenario with three classes and pd-multiindex mtype (6374) fkiraly

• [ENH] test classifiers on str dtype y, ensure predict returns same type and labels (6428) fkiraly

Transformations

• [ENH] Test Parameters for FinancialHolidaysTransformer (6334) sharma-kshitij-ks

• [ENH] ADI/CV feature extractor (6336) shlok191

• [ENH] Bollinger Bands (6473) ishanpai

Test framework

• [ENH] enable check_estimator and QuickTester.run_tests to work with skip marked pytest tests (6233) YelenaYY

• [ENH] make get_packages_with_changed_specs safe to mutation of return (6451) fkiraly

Visualization

• [ENH] plot_series improved to use matplotlib conventions; plot_interval can now plot multiple overlaid intervals (6416, 6501) ericjb

Documentation

• [DOC] remove redundant/duplicative classification tutorial notebooks (6401) fkiraly

• [DOC] update meetup time to new 1pm slot (6402) fkiraly

• [DOC] explanation of get_test_params in test framework example (6434) fkiraly

• [DOC] fix download badges in README (6479) fkiraly

• [DOC] improved formatting of transformation docstrings (6489) fkiraly

• [DOC] document more tags: transformations (6351) fkiraly

• [DOC] Improve docstrings for metrics (6419) fkiraly

• [DOC] fixed wrong sentence in the documentation (6375) helloplayer1

• [DOC] Correct docstring for conversion functions of dask_to_pd (6439) pranavvp16

• [DOC] Fix hugging face transformers documentation (6450`) benheid

• [DOC] plot_calibration docstring - formal explanation of the plot (6414) fkiraly

• [DOC] high-level explanation of deprecation policy principles (6464) fkiraly

Maintenance

• [MNT] [Dependabot](deps): Update holidays requirement from <0.49,>=0.29 to >=0.29,<0.50 (6456) dependabot[bot]

• [MNT] [Dependabot](deps): Update pycatch22 requirement from <0.4.4 to <0.4.6`` (6442) dependabot[bot]

• [MNT] [Dependabot](deps): Update sphinx-design requirement from <0.6.0 to <0.7.0 (6471) dependabot[bot]

• [MNT] [Dependabot](deps): Update dask requirement from <2024.5.1 to <2024.5.2 (6444) dependabot[bot]

• [MNT] [Dependabot](deps): Update dtw-python requirement from <1.5,>=1.3 to >=1.3,<1.6 (6474) dependabot[bot]

• [MNT] include unit tests in sktime/tests in per module tests (6353) yarnabrina

• [MNT] maintenance changes for AutoTBATS (6400) yarnabrina

• [MNT] bound transformers<4.41.0 (6447) fkiraly

• [MNT] sklearn 1.5.0 compatibility patch (6464) fkiraly

• [MNT] skip doctest for all_estimators (6476) fkiraly

• [MNT] address various deprecation and computation warnings (6482) fkiraly

• [MNT] address further deprecation warnings from pandas (6494) fkiraly

• [MNT] fix the docs local build failure due to corrupt notebook (6426) fnhirwa

Fixes

Forecasting

• [BUG] fix ForecastX when forecaster_X_exogeneous="complement" (6433) fnhirwa

• [BUG] Modified VAR code to allow predict_quantiles of 0.5 (fixes #4742) (6441) meraldoantonio

Neural networks

• [BUG] Remove duplicated BaseDeepNetworkPyTorch in networks.base (6398) luca-miniati

Time series classification

• [BUG] Resolve LSTMFCNClassifier changing callback parameter (6239) ArthrowAbstract

• [BUG] fix _get_train_probs in some classifiers to accept any input data type (6377) fkiraly

• [BUG] fix BaggingClassifier for column subsampling case (6429) fkiraly

• [BUG] fix ProximityForest, tree, stump, and IndividualBOSS returning y of different type in predict (6432) fkiraly

• [BUG] fix classifier default _predict returning integer labels always, even if fit y was not integer (6430) fkiraly

• [BUG] in CNNClassifier, ensure filter_sizes and padding is passed on (6452) fkiraly

• [BUG] fix BaseClassifier.fit_predict and fit_predict_proba for pd-multiindex mtype (6491) fkiraly

Time series regression

• [BUG] Resolve LSTMFCNRegressor changing callback parameter (6239) ArthrowAbstract

• [BUG] in CNNRegressor, ensure filter_sizes and padding is passed on (6452) fkiraly

Transformations

• [BUG] fix to make LabelEncoder compatible with sktime pipelines (6458) Abhay-Lejith

Test framework

• [BUG] allow metric classes to be called with multilevel arg if series is not hierarchical (6418) fkiraly

• [BUG] fix test_run_test_for_class logic check if ONLY_CHANGED_MODULES flag is False and all estimator dependencies are present (6383) fkiraly

• [BUG] fix test_run_test_for_class test logic (6448) fkiraly

Visualization

• [BUG] fix xticks fore date-like data in plot_series (6416, 6501) ericjb

Contributors

Abhay-Lejith, ArthrowAbstract, benHeid, cedricdonie, ericjb, fkiraly, fnhirwa, helloplayer1, ishanpai, luca-miniati, meraldoantonio, ninedigits, pranavvp16, sharma-kshitij-ks, shlok191, yarnabrina, YelenaYY

Kindly note the python 3.8 End-of-life warning below.

Maintenance release:

scheduled deprecations and change actions

optimization of test collection speed

For last non-maintenance content updates, see 0.28.1.

Dependency changes

sktime now requires scikit-base>=0.6.1 (core dependency), this has changed from previously no lower bound.

Deprecations and removals

Python 3.8 End-of-life

From sktime 0.30.0, sktime will require Python version >=3.9. No errors will be raised, but test coverage and support for Python 3.8 will be dropped from 0.30.0 onwards.

Kindly note for context: python 3.8 will reach end of life in October 2024, and multiple sktime core dependencies, including scikit-learn , have already dropped support for 3.8.

Forecasting

cINNForecaster has been renamed to CINNForecaster . The estimator is available under its past name at its current location until 0.30.0, when the old name will be removed. To prepare for the name change, replace any imports of cINNForecaster with imports of CINNForecaster .

Transformations

The n_jobs parameter in the Catch22 transformer has been removed. Users should pass parallelization backend parameters via set_config instead. To specify n_jobs , use any of the backends supporting it in the backend:parallel configuration, such as "loky" or "multithreading" . The n_jobs parameter should be passed via the backend:parallel:params configuration. To retain previous behaviour, with a specific setting of n_jobs=x , use set_config(**{"backend:parallel": "loky", "backend:parallel:params": {"n_jobs": x}}) .

Contents

[MNT] change cycle (0.29.0) for renaming cINNForecaster to CINNForecaster ( #6238 ) @geetu040

[MNT] python 3.8 End-of-life and sktime support drop warning ( #6348 ) @fkiraly

[MNT] speed up test collection - cache differential testing switch utilities ( #6357 ) @fkiraly , @yarnabrina

[MNT] temporary skip of estimators involved in timeouts #6344 ( #6361 ) @fkiraly

[MNT] 0.29.0 deprecations and change actions ( #6350 ) @fkiraly

Contributors

@fkiraly , @geetu040 , @yarnabrina

Highlights

Experimental Hugging Face interface for pre-trained forecasters and foundation models ( #5796 ) @benHeid

estimator tags are now systematically documented in the API reference ( #6289 ) @fkiraly

new classifiers, transformers from pyts interfaced: BOSSVS, learning shapelets, shapelet transform ( #6296 ) @johannfaouzi (author), @fkiraly (interface)

new classifiers from tslearn interfaced: time series SVC, SVR, learning shapelets ( #6273 ) @rtavenar (author), @fkiraly (interface)

ForecastX can now use use future-unknown exogenous variables if passed in predict ( #6199 ) @yarnabrina

bagging/bootstrap forecaster can now be applied to multivariate, exogeneous, hierarchical data and produces fully probabilistic forecasts ( #6052 ) @fkiraly

neuralforecast models now have settings to auto-detect date-time freq , and pass optimizer ( #6235 , #6237 ) @pranavvp16 , @geetu040

Dependency changes

dask (data container and parallelization back-end) bounds have been updated to <2024.4.2

arch (transformation and parameter estimation soft dependency) bounds have been updated to >=5.6,<7.1.0

holidays (transformations soft dependency) bounds have been updated to >=0.29,<0.48

mne (transformations soft dependency) bounds have been updated to >=1.5,<1.8

Core interface changes

All objects and estimators now can, in addition to the existing PEP 440 package dependency specifier tags, specify PEP 508 compatible environment markers for their dependencies, via the env_marker tag. Values should be PEP 508 compliant strings, e.g., platform_system!="Windows" .

This allows for more fine-grained control over the dependencies of estimators, where needed, e.g., for estimators that require specific operating systems.

Enhancements

BaseObject and base framework

[ENH] PEP 508 environment markers for estimators ( #6144 ) @fkiraly

[ENH] enhancements to tag system, systematic API docs for tags ( #6289 ) @fkiraly

Benchmarking, Metrics, Splitters

[ENH] instance splitter to apply sklearn splitter to panel data ( #6055 ) @fkiraly

[ENH] efficient _evaluate_by_index for MSE and RMSE ( MeanSquaredError ) ( #6248 ) @fkiraly

[ENH] implement efficient _evaluate_by_index for MedianAbsoluteError class ( #6251 ) @mobley-trent

Forecasting

[ENH] Hugging Face interface for pre-trained forecasters ( #5796 ) @benHeid

[ENH] bagging/bootstrap forecaster extended to multivariate, exogeneous, hierarchical data ( #6052 ) @fkiraly

[ENH] Minor neuralforecast related changes ( #6312 ) @yarnabrina

[ENH] Option to use future-unknown exogenous variables in ForecastX if passed in predict ( #6199 ) @yarnabrina

[ENH] Add optimizer param for neuralforecast models ( #6235 ) @pranavvp16

[ENH] Update behavior of freq="auto" in neuralforecast facing estimators ( #6237 ) @geetu040

[ENH] TBATS test parameters to cover doc example ( #6292 ) @fkiraly

Neural networks

[ENH] added test parameters to CNNNetwork and ResnetNetwork ( #6209 ) @julian-fong

[ENH] added test parameters for the LSTM FCNN network ( #6281 ) @shlok191

Probability distributions and simulators

[ENH] extend Empirical distribution to hierarchical data ( #6066 ) @fkiraly

[ENH] mixture distribution, from skpro ( #6179 ) @vandit98

Time series classification

[ENH] added test parameters for MatrixProfileClassifier ( #6193 ) @MMTrooper

[ENH] interfaces to further tslearn estimators ( #6273 ) @fkiraly

[ENH] interfaces to further pyts classifiers ( #6296 ) @fkiraly

Time series clustering

[ENH] clusterer test scenario with unequal length time series; fix clusterer tags ( #6277 ) @fkiraly

Time series regression

[ENH] k-nearest neighbors regressor: support for non-brute algorithms and non-precomputed mode to improve memory efficiency ( #6217 ) @Z-Fran

Transformations

[ENH] make TabularToSeriesAdaptor compatible with sklearn transformers that accept only y , e.g., LabelEncoder ( #5982 ) @fkiraly

Test framework

[ENH] make get_examples side effect safe via deepcopy ( #6259 ) @fkiraly

[ENH] refactor test scenario creation to be lazy rather than on module load ( #6278 ) @fkiraly

Documentation

[DOC] update installation instructions on conda soft dependencies ( #6229 ) @fkiraly

[DOC] add missing import statements to the InvertAugmenter docstring example ( #6236 ) @Anteemony

[DOC] Adding Usage Example in docstring ( #6264 ) @MihirsinhChauhan

[DOC] improve docstring formatting in probabilistic metrics ( #6256 ) @fkiraly

[DOC] authors tag - extension template instructions to credit 3rd party interfaced authors ( #5953 ) @fkiraly

[DOC] Refactor examples directory and link to docs/source/examples ( #6210 ) @duydl

[DOC] author credits to tslearn authors ( #6269 ) @fkiraly

[DOC] author credits to pyts authors ( #6270 ) @fkiraly

[DOC] Update README.md - time of Friday meetups ( #6293 ) @fkiraly

[DOC] systematic API docs for tags ( #6289 ) @fkiraly

[DOC] in extension templates, clarify handling of soft dependencies ( #6325 ) @fkiraly

[DOC] author credits to pycatch22 authors, fix missing documentation page ( #6300 ) @fkiraly

[DOC] added usage examples to multiple estimator docstrings ( #6187 ) @MihirsinhChauhan

[DOC] Miscellaneous aesthetic improvements to docs UI ( #6211 ) @duydl

[DOC] Remove redundant code in tutorial section 2.2.4 ( #6267 ) @iamSathishR

[DOC] Added an example to WhiteNoiseAugmenter ( #6200 ) @SamruddhiNavale

Maintenance

[MNT] Basic fix and enhancement of doc local build process ( #6128 ) @duydl

[MNT] temporary skip for failure #6260 ( #6262 ) @fkiraly

[MNT] Update dask requirement from <2024.2.2 to <2024.4.2 , add new required dataframe extra to pyproject.toml . ( #6282 ) @yarnabrina

[MNT] fix isolation of mlflow soft dependencies ( #6285 ) @fkiraly

[MNT] add @slavik57 as a maintenance contributor for fixing conda-forge sktime-all-extras 0.28.0 release ( #6308 ) @tm-slavik57

[MNT] set GHA macos runner consistently to macos-13 ( #6328 ) @fkiraly

[MNT] Dependabot: Update holidays requirement from <0.46,>=0.29 to >=0.29,<0.47 ( #6250 ) @dependabot[bot]

[MNT] Dependabot: Update holidays requirement from <0.47,>=0.29 to >=0.29,<0.48 ( #6302 ) @dependabot[bot]

[MNT] Dependabot: Update arch requirement from <6.4.0,>=5.6 to >=5.6,<7.1.0 ( #6307 , #6309 ) @dependabot[bot]

[MNT] Dependabot: Update pytest-xdist requirement from <3.6,>=3.3 to >=3.3,<3.7 ( #6316 ) @dependabot[bot]

[MNT] Dependabot: Update mne requirement from <1.7,>=1.5 to >=1.5,<1.8 ( #6317 ) @dependabot[bot]

[MNT] Update dask requirement from <2024.2.2 to <2024.4.2 , add new required dataframe extra to pyproject.toml . ( #6282 ) @yarnabrina

Fixes

Data loaders

[BUG] Fix tsf data error log and make it more precise ( #6258 ) @pranavvp16

Forecasting

[BUG] Fix NaiveForecaster with sp>1 ( #5923 ) @benHeid

[BUG] fix FallbackForecaster failing with ForecastByLevel when nan_predict_policy='raise' ( #6231 ) @ninedigits

[BUG] Add regression test for bug 3177 ( #6246 ) @benHeid

[BUG] fix failing test in neuralforecast auto freq, amid pandas freq deprecations ( #6321 ) @geetu040

Probability distributions and simulators

[BUG] fix var of Laplace distribution ( #6324 ) @fkiraly

[BUG] fix Empirical index to be pd.MultiIndex for hierarchical data index ( #6341 ) @fkiraly

Time series clustering

[BUG] fix dependent tags of TimeSeriesDBSCAN ( #6322 ) @fkiraly

Time series regression

[BUG] in CNNRegressor , fix self.model not found error when verbose=True ( #6232 ) @morestart

Transformations

[BUG] Imputer bugfix #6224 ( #6253 ) @Ram0nB

[BUG] Fix backfill of custom function in window_feature ( #6294 ) @toandaominh1997

[BUG] fixed indexing of return in TSBootstrapAdapter ( #6326 ) @astrogilda

[BUG] Fix STLTransformer.inverse_transform for univariate case ( #6338 ) @fkiraly

Contributors

@Anteemony , @astrogilda , @benHeid , @duydl , @fkiraly , @geetu040 , @iamSathishR , @julian-fong , @MihirsinhChauhan , @MMTrooper , @mobley-trent , @morestart , @ninedigits , @pranavvp16 , @Ram0nB , @SamruddhiNavale , @shlok191 , @slavik57 , @tm-slavik57 , @toandaominh1997 , @vandit98 , @yarnabrina , @Z-Fran

Highlights

• Experimental Hugging Face interface for pre-trained forecasters and foundation models (5796) benHeid

• estimator tags are now systematically documented in the API reference (6289) fkiraly

• new classifiers, transformers from pyts interfaced: BOSSVS, learning shapelets, shapelet transform (6296) johannfaouzi (author), fkiraly (interface)

• new classifiers from tslearn interfaced: time series SVC, SVR, learning shapelets (6273) rtavenar (author), fkiraly (interface)

• ForecastX can now use use future-unknown exogenous variables if passed in predict (6199) yarnabrina

• bagging/bootstrap forecaster can now be applied to multivariate, exogeneous, hierarchical data and produces fully probabilistic forecasts (6052) fkiraly

• neuralforecast models now have settings to auto-detect date-time freq, and pass optimizer (6235, 6237) pranavvp16, geetu040

Dependency changes

• dask (data container and parallelization back-end) bounds have been updated to <2024.4.2

• arch (transformation and parameter estimation soft dependency) bounds have been updated to >=5.6,<7.1.0

• holidays (transformations soft dependency) bounds have been updated to >=0.29,<0.48

• mne (transformations soft dependency) bounds have been updated to >=1.5,<1.8

Core interface changes

All objects and estimators now can, in addition to the existing PEP 440 package dependency specifier tags, specify PEP 508 compatible environment markers for their dependencies, via the env_marker tag. Values should be PEP 508 compliant strings, e.g., platform_system!="Windows".

This allows for more fine-grained control over the dependencies of estimators, where needed, e.g., for estimators that require specific operating systems.

Enhancements

BaseObject and base framework

• [ENH] PEP 508 environment markers for estimators (6144) fkiraly

• [ENH] enhancements to tag system, systematic API docs for tags (6289) fkiraly

Benchmarking, Metrics, Splitters

• [ENH] instance splitter to apply sklearn splitter to panel data (6055) fkiraly

• [ENH] efficient _evaluate_by_index for MSE and RMSE (MeanSquaredError) (6248) fkiraly

• [ENH] implement efficient _evaluate_by_index for MedianAbsoluteError class (6251) mobley-trent

Forecasting

• [ENH] Hugging Face interface for pre-trained forecasters (5796) benHeid

• [ENH] bagging/bootstrap forecaster extended to multivariate, exogeneous, hierarchical data (6052) fkiraly

• [ENH] Minor neuralforecast related changes (6312) yarnabrina

• [ENH] Option to use future-unknown exogenous variables in ForecastX if passed in predict (6199) yarnabrina

• [ENH] Add optimizer param for neuralforecast models (6235) pranavvp16

• [ENH] Update behavior of freq="auto" in neuralforecast facing estimators (6237) geetu040

• [ENH] TBATS test parameters to cover doc example (6292) fkiraly

Neural networks

• [ENH] added test parameters to CNNNetwork and ResnetNetwork (6209) julian-fong

• [ENH] added test parameters for the LSTM FCNN network (6281) shlok191

Probability distributions and simulators

• [ENH] extend Empirical distribution to hierarchical data (6066) fkiraly

• [ENH] mixture distribution, from skpro (6179) vandit98

Time series classification

• [ENH] added test parameters for MatrixProfileClassifier (6193) MMTrooper

• [ENH] interfaces to further tslearn estimators (6273) fkiraly

• [ENH] interfaces to further pyts classifiers (6296) fkiraly

Time series clustering

• [ENH] clusterer test scenario with unequal length time series; fix clusterer tags (6277) fkiraly

Time series regression

• [ENH] k-nearest neighbors regressor: support for non-brute algorithms and non-precomputed mode to improve memory efficiency (6217) Z-Fran

Transformations

• [ENH] make TabularToSeriesAdaptor compatible with sklearn transformers that accept only y, e.g., LabelEncoder (5982) fkiraly

Test framework

• [ENH] make get_examples side effect safe via deepcopy (6259) fkiraly

• [ENH] refactor test scenario creation to be lazy rather than on module load (6278) fkiraly

Documentation

• [DOC] update installation instructions on conda soft dependencies (6229) fkiraly

• [DOC] add missing import statements to the InvertAugmenter docstring example (6236) Anteemony

• [DOC] Adding Usage Example in docstring (6264) MihirsinhChauhan

• [DOC] improve docstring formatting in probabilistic metrics (6256) fkiraly

• [DOC] authors tag - extension template instructions to credit 3rd party interfaced authors (5953) fkiraly

• [DOC] Refactor examples directory and link to docs/source/examples (6210) duydl

• [DOC] author credits to tslearn authors (6269) fkiraly

• [DOC] author credits to pyts authors (6270) fkiraly

• [DOC] Update README.md - time of Friday meetups (6293) fkiraly

• [DOC] systematic API docs for tags (6289) fkiraly

• [DOC] in extension templates, clarify handling of soft dependencies (6325) fkiraly

• [DOC] author credits to pycatch22 authors, fix missing documentation page (6300) fkiraly

• [DOC] added usage examples to multiple estimator docstrings (6187) MihirsinhChauhan

• [DOC] Miscellaneous aesthetic improvements to docs UI (6211) duydl

• [DOC] Remove redundant code in tutorial section 2.2.4 (6267) iamSathishR

• [DOC] Added an example to WhiteNoiseAugmenter (6200) SamruddhiNavale

Maintenance

• [MNT] Basic fix and enhancement of doc local build process (6128) duydl

• [MNT] temporary skip for failure #6260 (6262) fkiraly

• [MNT] Update dask requirement from <2024.2.2 to <2024.4.2, add new required dataframe extra to pyproject.toml. (6282) yarnabrina

• [MNT] fix isolation of mlflow soft dependencies (6285) fkiraly

• [MNT] add slavik57 as a maintenance contributor for fixing conda-forge sktime-all-extras 0.28.0 release (6308) tm-slavik57

• [MNT] set GHA macos runner consistently to macos-13 (6328) fkiraly

• [MNT] [Dependabot](deps-dev): Update holidays requirement from <0.46,>=0.29 to >=0.29,<0.47 (6250) dependabot[bot]

• [MNT] [Dependabot](deps): Update holidays requirement from <0.47,>=0.29 to >=0.29,<0.48 (6302) dependabot[bot]

• [MNT] [Dependabot](deps): Update arch requirement from <6.4.0,>=5.6 to >=5.6,<7.1.0 (6307, 6309) dependabot[bot]

• [MNT] [Dependabot](deps): Update pytest-xdist requirement from <3.6,>=3.3 to >=3.3,<3.7 (6316) dependabot[bot]

• [MNT] [Dependabot](deps): Update mne requirement from <1.7,>=1.5 to >=1.5,<1.8 (6317) dependabot[bot]

• [MNT] Update dask requirement from <2024.2.2 to <2024.4.2, add new required dataframe extra to pyproject.toml. (6282) yarnabrina

Fixes

Data loaders

• [BUG] Fix tsf data error log and make it more precise (6258) pranavvp16

Forecasting

• [BUG] Fix NaiveForecaster with sp>1 (5923) benHeid

• [BUG] fix FallbackForecaster failing with ForecastByLevel when nan_predict_policy='raise' (6231) ninedigits

• [BUG] Add regression test for bug 3177 (6246) benHeid

• [BUG] fix failing test in neuralforecast auto freq, amid pandas freq deprecations (6321) geetu040

Probability distributions and simulators

• [BUG] fix var of Laplace distribution (6324) fkiraly

• [BUG] fix Empirical index to be pd.MultiIndex for hierarchical data index (6341) fkiraly

Time series clustering

• [BUG] fix dependent tags of TimeSeriesDBSCAN (6322) fkiraly

Time series regression

• [BUG] in CNNRegressor, fix self.model not found error when verbose=True (6232) morestart

Transformations

• [BUG] Imputer bugfix #6224 (6253) Ram0nB

• [BUG] Fix backfill of custom function in window_feature (6294) toandaominh1997

• [BUG] fixed indexing of return in TSBootstrapAdapter (6326) astrogilda

• [BUG] Fix STLTransformer.inverse_transform for univariate case (6338) fkiraly

Contributors

Anteemony, astrogilda, benHeid, duydl, fkiraly, geetu040, iamSathishR, julian-fong, MihirsinhChauhan, MMTrooper, mobley-trent, morestart, ninedigits, pranavvp16, Ram0nB, SamruddhiNavale, shlok191, slavik57, tm-slavik57, toandaominh1997, vandit98, yarnabrina, Z-Fran

Maintenance release:

scheduled deprecations and change actions

support for pandas 2.2.X

For last non-maintenance content updates, see 0.27.1.

Dependency changes

sktime now supports pandas 2.2.X , bounds have been updated to <2.3.0,>=1.1 .

temporian (transformations soft dependency) bounds have been updated to >=0.7.0,<0.9.0 .

pykalman-bardo dependencies have been replaced by the original fork pykalman . pykalman-bardo has been merged back into pykalman , which is no longer abandoned. This is a soft dependency, and the switch does not affect users installing sktime using one of its dependency sets.

Deprecations and removals

Forecasting

in ProphetPiecewiseLinearTrendForecaster , the seasonality parameters yearly_seasonality , weekly_seasonality and daily_seasonality now have default values of False . To retain previous behaviour, set these parameters explicitly to "auto" .

Transformations

The n_jobs parameter in the Catch22 transformer is deprecated and will be removed in 0.29.0. Users should pass parallelization backend parameters via set_config instead. To specify n_jobs , use any of the backends supporting it in the backend:parallel configuration, such as "loky" or "multithreading" . The n_jobs parameter should be passed via the backend:parallel:params configuration. To retain previous behaviour, with a specific setting of n_jobs=x , use set_config(**{"backend:parallel": "loky", "backend:parallel:params": {"n_jobs": x}}) .

The n_jobs parameter in the Catch22Wrapper transformer has been removed. Users should pass parallelization backend parameters via set_config instead. To specify n_jobs , use any of the backends supporting it in the backend:parallel configuration, such as "loky" or "multithreading" . The n_jobs parameter should be passed via the backend:parallel:params configuration. To retain previous behaviour, with a specific setting of n_jobs=x , use set_config(**{"backend:parallel": "loky", "backend:parallel:params": {"n_jobs": x}}) .

panel.dictionary_based.PAA has been renamed to PAAlegacy in 0.27.0, and sktime.transformations.series.PAA2 has been renamed to PAA . PAA is now the primary PAA implementation in sktime . After completion of the deprecation cycle, the estimators are no longer available under their previous names. To migrate dependent code to use the new names, do one of the following:

1. replace use of PAA from sktime.transformations.panel.dictionary_based by use of PAA2 from sktime.transformations.series.paa , switching parameter names appropriately, or
2. replace use of PAA from sktime.transformations.panel.dictionary_based by use of PAAlegacy from sktime.transformations.panel.dictionary_based , without change of parameter values.

panel.dictionary_based.SAX has been renamed to SAXlegacy in 0.27.0, while sktime.transformations.series.SAX2 has been renamed to SAX . SAX is now the primary SAX implementation in sktime , while the former SAX will continue to be available as SAXlegacy . After completion of the deprecation cycle, the estimators are no longer available under their previous names. To migrate dependent code to use the new names, do one of the following:

1. replace use of SAX from sktime.transformations.panel.dictionary_based by use of SAX2 from sktime.transformations.series.paa , switching parameter names appropriately, or
2. replace use of SAX from sktime.transformations.panel.dictionary_based by use of SAXlegacy from sktime.transformations.panel.dictionary_based , without change of parameter values.

Contents

[MNT] 0.28.0 deprecations and change actions ( #6198 ) @fkiraly

[MNT] raise pandas bound to pandas<2.3.0 ( #5841 ) @fkiraly

[MNT] update temporian bound to <0.9.0,!=0.8.0 ( #6222 ) @fkiraly

[MNT] revert switch from pykalman to pykalman-bardo ( #6114 ) @fkiraly

[MNT] Dependabot: Update pytest-cov requirement from <4.2,>=4.1 to >=4.1,<5.1 ( #6215 ) @dependabot[bot]

[MNT] Dependabot: Bump tj-actions/changed-files from 43 to 44 ( #6226 ) @dependabot[bot]

[ENH] stricter condition for get_test_params not failing in repo soft dependency isolation tests ( #6223 ) @fkiraly

Highlights

Phase 1 integration with temporian - TemporianTransformer transformer ( #5980 ) @ianspektor , @achoum , @javiber

Phase 1 integration with tsbootstrap - TSBootstrapAdapter transformer ( #5887 ) @benHeid , @astrogilda , @fkiraly

Shapelet transform from pyts available as sktime transformer ( #6082 ) @Abhay-Lejith

Catch22 transformer now supports short aliases and parallelization backend selection ( #6002 ) @julnow

forecasting tuners can now return performances of all parameters, via return_n_best_forecasters=-1 ( #6031 ) @HassnHamada

NeuralForecastRNN can now auto-detect freq ( #6039 ) @geetu040

time series splitters are now first-class objects, with suite tests and check_estimator support ( #6051 ) @fkiraly

Dependency changes

temporian is now a soft dependency for sktime (transformations)

holidays (transformations soft dependency) bounds have been updated to >=0.29,<0.46

dtw-python bounds have been updated to `` >=1.3,<1.5`

Core interface changes

time series splitters are now full first-class citizens. Interface conformance can now be checked with check_estimator .

Deprecations and removals

Forecasting

cINNForecaster will be renamed to CINNForecaster in sktime 0.29.0. The estimator is available under the future name at its current location, and will be available under its deprecated name until 0.30.0. To prepare for the name change, replace any imports of cINNForecaster with imports of CINNForecaster .

Enhancements

Benchmarking, Metrics, Splitters

[ENH] check_estimator integration for splitters ( #6051 ) @fkiraly

Data loaders

[ENH] automatic inference of file ending in data loaders for single file types ( #6045 ) @SaiRevanth25

Data types, checks, conversions

[ENH] use Index.unique instead of set in conversion from pd-multiindex to df-list mtype by @fkiraly ( #6007 )

Distances, kernels

[ENH] Second test parameter set for shapeDTW ( #6093 ) @XinyuWuu

[ENH] add colalign functionality to ScipyDist class as specified in the docstrings ( #6110 ) @fnhirwa

Forecasting

[ENH] forecasting tuners, return_n_best_forecasters=-1 to return performances of all forecasters ( #6031 ) @HassnHamada

[ENH] NeuralForecastRNN freq auto-detect feature ( #6039 ) @geetu040

[ENH] neuralforecast based LSTM model by @pranavvp16 ( #6047 )

[ENH] fix ForecastingHorizon.freq handling for pandas 2.2.X by @fkiraly ( #6057 )

Neural network templates

[ENH] added test params to RNNNetwork ( #6155 ) @julian-fong

Time series classification

[ENH] remove private methods from parameters of ProximityForest , ProximityTree , and ProximityStump by @fnhirwa ( #6046 )

Time series clustering

[ENH] add new test parameter sets for TimeSeriesKMeansTslearn ( #6195 ) @shankariraja

Time series regression

[ENH] Migrate DL regressors from sktime-dl : CNTC, InceptionTime, MACNN ( #6038 ) @nilesh05apr

[ENH] MultiplexRegressor - autoML multiplexer for time series regressors ( #6075 ) @ksharma6

Transformations

[ENH] tsbootstrap transformer adapter ( #5887 ) @benHeid

[ENH] TemporianTransformer - interface to temporian ( #5980 ) @ianspektor , @achoum

[ENH] Refactored and improved Catch22 transformer - support for column names, short aliases, refactor to pd.Series , sktime native parallelization ( #6002 ) @julnow

[ENH] Examples for YtoX transformer ( #6028 , #6059 ) @fkiraly , @geetu040

[ENH] Shapelet transform interfacing pyts ( #6082 ) @Abhay-Lejith

[ENH] Add a test_mstl module checking if transform returns desired components by @kcentric ( #6084 )

[ENH] add test cases for HampelFilter by @fkiraly ( #6087 )

[ENH] Second test parameter set for Kalman Filter ( #6095 ) @XinyuWuu

[ENH] Add MSTL import statement in detrend by @geetu040 ( #6116 )

Test framework

[ENH] test suite for splitters ( #6051 ) @fkiraly

Documentation

[DOC] Fix invalid use of single-grave in docstrings ( #6023 ) @geetu040

[DOC] Fix typos in changelog by @yarnabrina ( #6034 )

[DOC] corrected Discord channel mention in developer guide ( #6163 ) @shankariraja

[DOC] add credit to @rikstarmans in ``FallbackForecaster` ( #6069 ) @fkiraly

[DOC] Added an example to MLPRegressor #4264 ( #6135 ) @vandit98

[DOC] in BaseSeriesAnnotator , document the int_label option ( #6143 ) @Alex-JG3

[DOC] fix typo in _registry.py ( #6160 ) @pranavvp16

[DOC] minor clarifications in mtype descriptions ( #6078 ) @fkiraly

[DOC] ExponentialSmoothing default method change from L-BFGS-B to SLSQP ( #6186 ) @manuel-munoz-aguirre

[DOC] fix missing exports in time series regression API ref ( #6191 ) @fkiraly

[DOC] add more examples to CoC from python software foundation CoC ( #6185 ) @fkiraly

[DOC] correct deprecation versions in BaseDeepClassifier docstring ( #6197 ) @fkiraly

[DOC] update maintainer tag information in docs and PR template ( #6072 ) @fkiraly

[DOC] Add hall-of-fame widget to README (Added the Hall-of-fame section) #3716 ( #6203 ) @KaustubhUp025

[DOC] Added docstring example to DummyClassifier ( #6146 ) @YashKhare20

[DOC] Added docstring for lstmfcn and MLP classifiers ( #6136 ) @vandit98

[DOC] Fix syntax error in “getting started” example code block for Time Series Regression ( #6022 ) @sahusiddharth

[DOC] Added blank lines to properly render FourierFeatures docstring, sp_list ( #5984 ) @tiloye

[DOC] add missing author credits of @ivarzap ( #6050 ) @fkiraly

[DOC] fix various typos ( #6043 ) @fkiraly

[DOC] clarification regarding immutability of self -params in extension templates ( #6053 ) @fkiraly

[DOC] Fix invalid use of single-grave in docstrings ( #6023 ) @geetu040

[DOC] Added docstring example to CNNRegressor ( #6102 ) @meraldoantonio

[DOC] corrected Discord channel mention in developer guide ( #6163 ) @shankariraja

[DOC] add credit to @rikstarmans in FallbackForecaster ( #6069 ) @fkiraly

[DOC] Added an example to MLPRegressor ( #6135 ) @vandit98

[DOC] fix typo in _registry.py ( #6160 ) @pranavvp16

[DOC] minor clarifications in mtype descriptions by @fkiraly ( #6078 )

[DOC] ExponentialSmoothing - fix docstring after default method change from L-BFGS-B to SLSQP`` ( #6186 ) @manuel-munoz-aguirre

[DOC] fix missing imports in time series regression API ref ( #6191 ) @fkiraly

[DOC] add more examples to CoC from python software foundation CoC ( #6185 ) @fkiraly

[DOC] correct deprecation versions in BaseDeepClassifier docstring ( #6197 ) @fkiraly

[DOC] update maintainer tag information in docs and PR template ( #6072 ) @fkiraly

[DOC] Add hall-of-fame widget and section to README ( #6203 ) @KaustubhUp025

Maintenance

[MNT] Dependabot: Update holidays requirement from <0.45,>=0.29 to >=0.29,<0.46 ( #6164 ) @dependabot[bot]

[MNT] Dependabot: Update dtw-python requirement from <1.4,>=1.3 to >=1.3,<1.5 ( #6165 ) @dependabot[bot]

[MNT] Dependabot: Bump tj-actions/changed-files from 42 to 43 ( #6125 ) @dependabot[bot]

[MNT] temporary skip sporadically failing tests for ShapeletTransformPyts ( #6172 ) @fkiraly

[MNT] create build tool to check invalid backticks ( #6088 ) @geetu040

[MNT] decouple catch22 module from numba utilities ( #6101 ) @fkiraly

[MNT] bound temporian<0.8.0 ( #6184 ) @fkiraly

[MNT] Ensure Update Contributors does not run on main ( #6189 ) @Greyisheep , @duydl

[MNT] initialize change cycle (0.28.0) for renaming cINNForecaster to CINNForecaster ( #6121 ) @geetu040

[MNT] Fix failing tests due to tensorflow update ( #6098 ) @benHeid

[MNT] silence sporadic failure in test_evaluate_error_score ( #6058 ) @fkiraly

[MNT] update statsforecast version in forecasting extra ( #6064 ) @yarnabrina

[MNT] Docker files updated by ( #6076 ) @deysanjeeb

[MNT] deprecation action timing for Catch22 changes ( #6123 ) @fkiraly

[MNT] run update-contributors workflow only on PR by ( #6133 ) @fkiraly

[MNT] temporary skip sporadically failing tests for ShapeletTransformPyts ( #6172 ) @fkiraly

[MNT] enable concurrency settings in ‘Install and Test’ GHA workflow ( #6074 ) @MEMEO-PRO

[MNT] temporary skip for some sporadic failures on main ( #6208 ) @fkiraly

Fixes

Distances, kernels

[BUG] Fix various issues in shapeDTW ( #6093 ) @XinyuWuu

[BUG] resolve redundant or problematic statements in numba bounding matrix routines ( #6183 ) @albertoazzari

Estimator registry

[BUG] remove unnecessary line in all_estimators ( #6103 ) @fkiraly

Forecasting

[BUG] Fixed SARIMAX failure when X is passed to predict but not fit ( #6005 ) @Abhay-Lejith

[BUG] fix BaseForecaster.predict_var default if predict_proba is implemented ( #6067 ) @fkiraly

[BUG] In ForecastingHorizon , ignore ValueError on pd.infer_freq when index has fewer than 3 values ( #6097 ) @tpvasconcelos

Time series classification

[BUG] fix super calls in deep learning classifiers and regressors ( #6139 ) @fkiraly

[BUG] Resolved wrong arg name lr in SimpleRNNClassifier and regressor, fix minor batch_size param issue in ResNetClassifier ( #6154 ) @vandit98

Time series regression

[BUG] fix BaseRegressor.score method failing with sklearn.metrics r2_score got an unexpected keyword argument 'normalize ( #6019 ) @Cyril-Meyer

[BUG] fix super calls in deep learning classifiers and regressors ( #6139 ) @fkiraly

[BUG] fix network construction in InceptionTimeRegressor ( #6140 ) @fkiraly

Transformations

[BUG] fix FeatureUnion for primitive outputs ( #6079 ) @fkiraly , @fspinna

[BUG] Fix unexpected NaN values in Summarizer ( #6081 ) @ShreeshaM07

[BUG] Update _shapelet_transform_numba.py to improve numerical stability ( #6141 ) @stevcabello

Test framework

[BUG] fix deep_equals when comparing ForecastingHorizon of different lengths by @MBristle ( #5954 )

Webpage

[BUG] fix search function for estimator overview not working ( #6105 ) @duydl

Contributors

@Abhay-Lejith , @achoum , @albertoazzari , @Alex-JG3 , @astrogilda , @benHeid , @Cyril-Meyer , @deysanjeeb , @duydl , @fkiraly , @fnhirwa , @fspinna , @geetu040 , @Greyisheep , @HassnHamada , @ianspektor , @javiber , @julian-fong , @julnow , @KaustubhUp025 , @kcentric , @ksharma6 , @manuel-munoz-aguirre , @MBristle , @MEMEO-PRO , @meraldoantonio , @nilesh05apr , @pranavvp16 , @SaiRevanth25 , @sahusiddharth , @shankariraja , @stevcabello , @tiloye , @tpvasconcelos , @vandit98 , @XinyuWuu , @YashKhare20

Highlights

• Phase 1 integration with temporian - TemporianTransformer transformer (5980) ianspektor, achoum, javiber

• Phase 1 integration with tsbootstrap - TSBootstrapAdapter transformer (5887) benHeid, astrogilda, fkiraly

• Shapelet transform from pyts available as sktime transformer (6082) Abhay-Lejith

• Catch22 transformer now supports short aliases and parallelization backend selection (6002) julnow

• forecasting tuners can now return performances of all parameters, via return_n_best_forecasters=-1 (6031) HassnHamada

• NeuralForecastRNN can now auto-detect freq (6039) geetu040

• time series splitters are now first-class objects, with suite tests and check_estimator support (6051) fkiraly

Dependency changes

• temporian is now a soft dependency for sktime (transformations)

• holidays (transformations soft dependency) bounds have been updated to >=0.29,<0.46

• dtw-python bounds have been updated to ``>=1.3,<1.5`

Core interface changes

• time series splitters are now full first-class citizens. Interface conformance can now be checked with check_estimator.

Deprecations and removals

Forecasting

cINNForecaster will be renamed to CINNForecaster in sktime 0.29.0. The estimator is available under the future name at its current location, and will be available under its deprecated name until 0.30.0. To prepare for the name change, replace any imports of cINNForecaster with imports of CINNForecaster.

Enhancements

Benchmarking, Metrics, Splitters

• [ENH] check_estimator integration for splitters (6051) fkiraly

Data loaders

• [ENH] automatic inference of file ending in data loaders for single file types (6045) SaiRevanth25

Data types, checks, conversions

• [ENH] use Index.unique instead of set in conversion from pd-multiindex to df-list mtype by fkiraly (6007)

Distances, kernels

• [ENH] Second test parameter set for shapeDTW (6093) XinyuWuu

• [ENH] add colalign functionality to ScipyDist class as specified in the docstrings (6110) fnhirwa

Forecasting

• [ENH] forecasting tuners, return_n_best_forecasters=-1 to return performances of all forecasters (6031) HassnHamada

• [ENH] NeuralForecastRNN freq auto-detect feature (6039) geetu040

• [ENH] neuralforecast based LSTM model by pranavvp16 (6047)

• [ENH] fix ForecastingHorizon.freq handling for pandas 2.2.X by fkiraly (6057)

Neural network templates

• [ENH] added test params to RNNNetwork (6155) julian-fong

Time series classification

• [ENH] remove private methods from parameters of ProximityForest, ProximityTree, and ProximityStump by fnhirwa (6046)

Time series clustering

• [ENH] add new test parameter sets for TimeSeriesKMeansTslearn (6195) shankariraja

Time series regression

• [ENH] Migrate DL regressors from sktime-dl: CNTC, InceptionTime, MACNN (6038) nilesh05apr

• [ENH] MultiplexRegressor - autoML multiplexer for time series regressors (6075) ksharma6

Transformations

• [ENH] tsbootstrap transformer adapter (5887) benHeid

• [ENH] TemporianTransformer - interface to temporian (5980) ianspektor, achoum

• [ENH] Refactored and improved Catch22 transformer - support for column names, short aliases, refactor to pd.Series, sktime native parallelization (6002) julnow

• [ENH] Examples for YtoX transformer (6028, 6059) fkiraly, geetu040

• [ENH] Shapelet transform interfacing pyts (6082) Abhay-Lejith

• [ENH] Add a test_mstl module checking if transform returns desired components by kcentric (6084)

• [ENH] add test cases for HampelFilter by fkiraly (6087)

• [ENH] Second test parameter set for Kalman Filter (6095) XinyuWuu

• [ENH] Add MSTL import statement in detrend by geetu040 (6116)

Test framework

• [ENH] test suite for splitters (6051) fkiraly

Documentation

• [DOC] Fix invalid use of single-grave in docstrings (6023) geetu040

• [DOC] Fix typos in changelog by yarnabrina (6034)

• [DOC] corrected Discord channel mention in developer guide (6163) shankariraja

• [DOC] add credit to rikstarmans in`FallbackForecaster`` (6069) fkiraly

• [DOC] Added an example to MLPRegressor #4264 (6135) vandit98

• [DOC] in BaseSeriesAnnotator, document the int_label option (6143) Alex-JG3

• [DOC] fix typo in _registry.py (6160) pranavvp16

• [DOC] minor clarifications in mtype descriptions (6078) fkiraly

• [DOC] ExponentialSmoothing default method change from L-BFGS-B to SLSQP (6186) manuel-munoz-aguirre

• [DOC] fix missing exports in time series regression API ref (6191) fkiraly

• [DOC] add more examples to CoC from python software foundation CoC (6185) fkiraly

• [DOC] correct deprecation versions in BaseDeepClassifier docstring (6197) fkiraly

• [DOC] update maintainer tag information in docs and PR template (6072) fkiraly

• [DOC] Add hall-of-fame widget to README (Added the Hall-of-fame section) #3716 (6203) KaustubhUp025

• [DOC] Added docstring example to DummyClassifier (6146) YashKhare20

• [DOC] Added docstring for lstmfcn and MLP classifiers (6136) vandit98

• [DOC] Fix syntax error in "getting started" example code block for Time Series Regression (6022) sahusiddharth

• [DOC] Added blank lines to properly render FourierFeatures docstring, sp_list (5984) tiloye

• [DOC] add missing author credits of ivarzap (6050) fkiraly

• [DOC] fix various typos (6043) fkiraly

• [DOC] clarification regarding immutability of self-params in extension templates (6053) fkiraly

• [DOC] Fix invalid use of single-grave in docstrings (6023) geetu040

• [DOC] Added docstring example to CNNRegressor (6102) meraldoantonio

• [DOC] corrected Discord channel mention in developer guide (6163) shankariraja

• [DOC] add credit to rikstarmans in FallbackForecaster (6069) fkiraly

• [DOC] Added an example to MLPRegressor (6135) vandit98

• [DOC] fix typo in _registry.py (6160) pranavvp16

• [DOC] minor clarifications in mtype descriptions by fkiraly (6078)

• [DOC] ExponentialSmoothing - fix docstring after default method change from L-BFGS-B to SLSQP`` (6186) manuel-munoz-aguirre

• [DOC] fix missing imports in time series regression API ref (6191) fkiraly

• [DOC] add more examples to CoC from python software foundation CoC (6185) fkiraly

• [DOC] correct deprecation versions in BaseDeepClassifier docstring (6197) fkiraly

• [DOC] update maintainer tag information in docs and PR template (6072) fkiraly

• [DOC] Add hall-of-fame widget and section to README (6203) KaustubhUp025

Maintenance

• [MNT] [Dependabot](deps-dev): Update holidays requirement from <0.45,>=0.29 to >=0.29,<0.46 (6164) dependabot[bot]

• [MNT] [Dependabot](deps-dev): Update dtw-python requirement from <1.4,>=1.3 to >=1.3,<1.5 (6165) dependabot[bot]

• [MNT] [Dependabot](deps): Bump tj-actions/changed-files from 42 to 43 (6125) dependabot[bot]

• [MNT] temporary skip sporadically failing tests for ShapeletTransformPyts (6172) fkiraly

• [MNT] create build tool to check invalid backticks (6088) geetu040

• [MNT] decouple catch22 module from numba utilities (6101) fkiraly

• [MNT] bound temporian<0.8.0 (6184) fkiraly

• [MNT] Ensure Update Contributors does not run on main (6189) Greyisheep, duydl

• [MNT] initialize change cycle (0.28.0) for renaming cINNForecaster to CINNForecaster (6121) geetu040

• [MNT] Fix failing tests due to tensorflow update (6098) benHeid

• [MNT] silence sporadic failure in test_evaluate_error_score (6058) fkiraly

• [MNT] update statsforecast version in forecasting extra (6064) yarnabrina

• [MNT] Docker files updated by (6076) deysanjeeb

• [MNT] deprecation action timing for Catch22 changes (6123) fkiraly

• [MNT] run update-contributors workflow only on PR by (6133) fkiraly

• [MNT] temporary skip sporadically failing tests for ShapeletTransformPyts (6172) fkiraly

• [MNT] enable concurrency settings in 'Install and Test' GHA workflow (6074) MEMEO-PRO

• [MNT] temporary skip for some sporadic failures on main (6208) fkiraly

Fixes

Distances, kernels

• [BUG] Fix various issues in shapeDTW (6093) XinyuWuu

• [BUG] resolve redundant or problematic statements in numba bounding matrix routines (6183) albertoazzari

Estimator registry

• [BUG] remove unnecessary line in all_estimators (6103) fkiraly

Forecasting

• [BUG] Fixed SARIMAX failure when X is passed to predict but not fit (6005) Abhay-Lejith

• [BUG] fix BaseForecaster.predict_var default if predict_proba is implemented (6067) fkiraly

• [BUG] In ForecastingHorizon, ignore ValueError on pd.infer_freq when index has fewer than 3 values (6097) tpvasconcelos

Time series classification

• [BUG] fix super calls in deep learning classifiers and regressors (6139) fkiraly

• [BUG] Resolved wrong arg name lr in SimpleRNNClassifier and regressor, fix minor batch_size param issue in ResNetClassifier (6154) vandit98

Time series regression

• [BUG] fix BaseRegressor.score method failing with sklearn.metrics r2_score got an unexpected keyword argument 'normalize (6019) Cyril-Meyer

• [BUG] fix super calls in deep learning classifiers and regressors (6139) fkiraly

• [BUG] fix network construction in InceptionTimeRegressor (6140) fkiraly

Transformations

• [BUG] fix FeatureUnion for primitive outputs (6079) fkiraly, fspinna

• [BUG] Fix unexpected NaN values in Summarizer (6081) ShreeshaM07

• [BUG] Update _shapelet_transform_numba.py to improve numerical stability (6141) stevcabello

Test framework

• [BUG] fix deep_equals when comparing ForecastingHorizon of different lengths by MBristle (5954)

Webpage

• [BUG] fix search function for estimator overview not working (6105) duydl

Contributors

Abhay-Lejith, achoum, albertoazzari, Alex-JG3, astrogilda, benHeid, Cyril-Meyer, deysanjeeb, duydl, fkiraly, fnhirwa, fspinna, geetu040, Greyisheep, HassnHamada, ianspektor, javiber, julian-fong, julnow, KaustubhUp025, kcentric, ksharma6, manuel-munoz-aguirre, MBristle, MEMEO-PRO, meraldoantonio, nilesh05apr, pranavvp16, SaiRevanth25, sahusiddharth, shankariraja, stevcabello, tiloye, tpvasconcelos, vandit98, XinyuWuu, YashKhare20