Changelog#

All notable changes to this project will be documented in this file. We keep track of changes in this file since v0.4.0. The format is based on Keep a Changelog and we adhere to Semantic Versioning. The source code for all releases is available on GitHub.

Note

To stay up-to-date with sktime releases, subscribe to sktime here or follow us on Twitter.

For upcoming changes and next releases, see our milestones. For our long-term plan, see our Roadmap.

Version 0.11.4 - 2022-05-13#

Highlights#

  • maintenance update for compatibility with recent scikit-learn 1.1.0 release

Dependency changes#

  • Added defensive upper bound scikit-learn<1.2.0

Maintenance#

Enhancements#

BaseObject#

  • [ENH] components retrieval utility and default BaseForecaster._update(update_params=False) for composites (#2596) @fkiraly

Clustering#

Data types, checks, conversions#

  • [ENH] more informative error message from mtype if no mtype can be identified (#2606) @fkiraly

Distances, kernels#

Forecasting#

  • [ENH] Extended sliding and expanding window splitters to allow timdelta forecasting horizon (#2551) @khrapovs

  • [ENH] Removed interval_width parameter of Prophet (#2630) @phershbe

Time series classification#

Transformations#

Fixes#

BaseObject#

Clustering#

Forecasting#

  • [BUG] Forecasting pipeline get/set params fixed for dunder generated pipelines (#2619) @fkiraly

Testing framework#

  • [BUG] fixing side effects between test runs of the same test in the test suite (#2558) @fkiraly

Contributors#

@chrisholder, @ciaran-g, @fkiraly, @khrapovs, @miraep8, @phershbe, @Ris-Bali, @TonyBagnall

Version 0.11.3 - 2022-04-29#

Highlights#

  • sktime is now compatible with scipy 1.8.X versions (#2468, #2474) @fkiraly

  • dunder method for forecasting pipelines: write trafo * forecaster * my_postproc for TransformedTargetForecaster pipeline (#2404) @fkiraly

  • dunder method for multiplexing/autoML: write forecaster1 | forecaster2 | forecaster3 for MultiplexForecaster, used in tuning over forecasters (#2540) @miraep8

  • dunders combine with existing transformer pipeline and feature union, e.g., trafo1 * trafo2 * forecaster or (trafo1 + trafo2) * forecaster

  • prediction intervals for UnobservedComponents forecaster (#2454) @juanitorduz

  • new argument return_tags of all_estimators allows listing estimators together with selected tags (#2410) @miraep8

Dependency changes#

  • Upper bound on scipy relaxed to scipy<1.9.0, sktime is now compatible with scipy 1.8.X versions.

Core interface changes#

All Estimators#

All estimators now have a reset method which resets objects a clean post-init state, keeping hyper-parameters. Equivalent to clone but overwrites self.

Forecasting#

Forecasters have two new dunder methods. Invoke dunders for easy creation of a pipeline object:

  • * with a transformer creates forecasting pipeline, e.g., my_trafo1 * my_forecaster * my_postproc. Transformers before the forecaster are used for pre-processing in a TransformedTargetForecaster. Transformers after the forecaster are used for post-processing in a TransformedTargetForecaster.

  • | with another forecaster creates a multiplexer, e.g., forecaster1 | forecaster2 | forecaster 3. Result is of class MultiplexForecaster which can be combined with grid search for autoML style tuning.

Dunder methods are compatible with existing transformer dunders * (pipeline) and + (feature union).

Forecaster update_predict now accepts an additional boolean argument reset_forecaster. If reset_forecaster = True (default and current intended behaviour), forecaster state does not change. If reset_forecaster = False, then update, predict sequence updates state.

In 0.13.0, the default will change to reset_forecaster = False.

Deprecations#

Forecasting#

Forecaster update_predict default behaviour will change from reset_forecaster = True to reset_forecaster = False, from 0.13.0 (see above).

Transformations#

Differencer: drop_na argument will be deprecated from 0.12.0 and removed in 0.13.0. It will be replaced bz the na_handling argument and a default of "fill_zero".

WindowSummarizer: lag_config will be deprecated from 0.12.0 and removed in 0.13.0. It will be replaced by the lag_feature argument and new specification syntax for it.

Enhancements#

BaseObject#

Data types, checks, conversions#

  • [ENH] new _make_panel utility, separate from _make_panel_X, with arbitrary return mtype (#2505) @fkiraly

Forecasting#

  • [ENH] prediction intervals for UnobservedComponents forecaster (#2454) @juanitorduz

  • [ENH] remove error message on exogeneous X from DirRec reducer (#2463) @fkiraly

  • [ENH] replace np.arange by np.arghwere in splitters to enable time based indexing and selection (#2394) @khrapovs

  • [ENH] Test SingleWindowSplitter with Timedelta forecasting horizon (#2392) @khrapovs

  • [ENH] Aggregator: remove index naming requirement (#2479) @ciaran-g

  • [ENH] MultiplexForecaster compatibility with multivariate, probabilistic and hierarchical forecasting (#2458) @fkiraly

  • [ENH] Differencer NA handling - “fill zero” parameter (#2487) @fkiraly

  • [ENH] Add random_state to statsmodels adapter and estimators (#2440) @ris-bali

  • [ENH] Added tests for MultiplexForecaster (#2520) @miraep8

  • [ENH] Added | dunder method for MultiplexForecaster (#2540) @miraep8

Registry#

  • [ENH] add new argument return_tags to all_estimators (#2410) @miraep8

Testing framework#

Transformations#

Fixes#

Clustering#

  • [BUG] Fixed medoids in kmedoids being taken across all data instead of cluster-wise (#2548) @chrisholder

Data types, checks, conversions#

  • [BUG] fixing direct conversions from/to numpyflat mtype being overriden by indirect ones (#2517) @fkiraly

Distances, kernels#

  • [BUG] Distances fixed bug where bounding matrix was being rounded incorrectly (#2549) @chrisholder

Forecasting#

  • [BUG] refactor _predict_moving_cutoff and bugfix, outer update_predict_single should be called (#2466) @fkiraly

  • [BUG] fix ThetaForecaster.predict_quantiles breaking on pd.DataFrame input (#2529) @fkiraly

  • [BUG] bugfix for default _predict_var implementation (#2538) @fkiraly

  • [BUG] ensure row index names are preserved in hierarchical forecasting when vectorizing (#2489) @fkiraly

  • [BUG] Fix type checking error due to pipeline type polymorphism when constructing nested pipelines (#2456) @fkiraly

  • [BUG] fix for update_predict state handling bug, replace detached cutoff by deepcopy (#2557) @fkiraly

  • [BUG] Fixes the index name dependencies in WindowSummarizer (#2567) @ltsaprounis

  • [BUG] Fix non-compliant output of ColumnEnsembleForecaster.pred_quantiles, pred_interval (#2512) @eenticott-shell

Time series classification#

  • [BUG] fixed ColumnEnsembleClassifier handling of unequal length data (#2513) @fkiraly

Transformations#

  • [BUG] remove alpha arg from _boxcox, remove private method dependencies, ensure scipy 1.8.0 compatibility (#2468) @fkiraly

  • [BUG] fix random state overwrite in MiniRocketMultivariate (#2563) @fkiraly

Testing framework#

  • [BUG] fix accidental overwrite of default method/arg sequences in test scenarios (#2457) @fkiraly

Refactored#

  • [ENH] changed references to fit-in-transform to fit_is_empty (#2494) @fkiraly

  • [ENH] cleaning up _panel._convert module (#2519) @fkiraly

  • [ENH] Legacy test refactor - move test_data_processing, mtype handling in test_classifier_output (#2506) @fkiraly

  • [ENH] MockForecaster without logging, MockUnivariateForecaster clean-up (#2539) @fkiraly

  • [ENH] metrics rework part I - output format tests (#2496) @fkiraly

  • [ENH] simplify load_from_tsfile, support more mtypes (#2521) @fkiraly

  • [ENH] removing dead args and functions post _predict_moving_cutoff refactor (#2470) @fkiraly

Maintenance#

  • [MNT] upgrade codecov uploader and cleanup coverage reporting (#2389) @tarpas

  • [MNT] fix soft dependency handling for esig imports (#2414) @fkiraly

  • [MNT] Make the contrib module private (#2422) @MatthewMiddlehurst

  • [MNT] disabling aggressive dtw_python import message (#2439) @KatieBuc

  • [MNT] loosen strict upper bound on scipy to 1.9.0 (#2474) @fkiraly

  • [MNT] Remove accidentally committed prob integration notebook (#2476) @eenticott-shell

  • [MNT] speed up Facebook Prophet tests (#2497) @fkiraly

  • [MNT] Proximity forest faster test param settings (#2525) @fkiraly

  • [MNT] Fix tests to prevent all guaranteed check_estimator failures (#2411) @danbartl

  • [MNT] added pytest-timeout time limit of 10 minutes (#2532, #2541) @fkiraly

  • [MNT] turn on tests for no state change in transform, predict (#2536) @fkiraly

  • [MNT] switch scipy mirror to anaconda on windows to resolve gfortran FileNotFoundError in all CI/CD (#2561) @fkiraly

  • [MNT] Add a script to generate changelog in rst format (#2449) @lmmentel

Documentation#

  • [DOC] Added clustering module to API docs (#2429) @aiwalter

  • [DOC] updated datatypes notebook (#2492) @fkiraly

  • [DOC] Broken Links in Testing Framework Doc (#2450) @Tomiiwa

  • [DOC] remove GSoC announcement from landing page after GSoC deadline (#2543) @GuzalBulatova

  • [DOC] fix typo in sktime install instructions, causes “invalid requirement error” if followed verbatim (#2503) @Samuel-Oyeneye

Contributors#

@aiwalter, @chrisholder, @ciaran-g, @danbartl, @eenticott-shell, @fkiraly, @GuzalBulatova, @juanitorduz, @KatieBuc, @khrapovs, @lmmentel, @ltsaprounis, @MatthewMiddlehurst, @miraep8, @ris-bali, @Samuel-Oyeneye, @tarpas, @Tomiiwa

Version 0.11.2 - 2022-04-11#

Fixes#

  • [BUG] temp workaround for unnamed levels in hierarchical X passed to aggregator (#2432) @fkiraly

  • [BUG] forecasting pipeline dunder fix by (#2431) @fkiraly

  • [BUG] fix erroneous direct passthrough in ColumnEnsembleForecaster (#2436) @fkiraly

  • [BUG] Incorrect indices returned by make_reduction on hierarchical data fixed by (#2438) @danbartl

Version 0.11.1 - 2022-04-10#

Highlights#

  • GSoC 2022 application instructions - apply by Apr 19 for GSoC with sktime! (#2373) @lmmentel @Lovkush-A @fkiraly

  • enhancements and bugfixes for probabilistic and hierarchical forecasting features introduced in 0.11.0

  • reconciliation transformers for hierarchical predictions (#2287, #2292) @ciaran-g

  • pipeline, tuning and evaluation compabitility for probabilistic forecasting (#2234, #2318) @eenticott-shell @fkiraly

  • interface to statsmodels SARIMAX (#2400) @TNTran92

  • reduction with transform-on-y predictors (e.g., lags, window summaries), and for hierarchical data (#2396) @danbartl

Core interface changes#

Data types, checks, conversions#

  • the pd-multiindex mtype was relaxed to allow arbitrary level names

Forecasting#

  • probabilistic forecasting interface now also available for auto-vectorization cases

  • probabilistic forecasting interface now compatible with hierarchical forecasting interface

Enhancements#

Data types, checks, conversions#

  • [ENH] tsf loader to allow specification of return mtype (#2103) @ltsaprounis

  • [ENH] relax name rules for multiindex - fixed omission in from_multi_index_to_nested (#2384) @ltsaprounis

Forecasting#

  • [ENH] require uniqueness from multiple alpha/coverage in interval/quantile forecasts (#2326) @fkiraly

  • [ENH] Adding fit parameters to VAR constructor #1850 (#2304) @TNTran92

  • [ENH] vectorization for probabilistic forecasting methods that return pd.DataFrame (#2355) @fkiraly

  • [ENH] adding compatibility with probabilistic and hierarchical forecasts to ForecastingPipeline and TransformedTargetForecaster (#2318) @fkiraly

  • [ENH] Allow pd.Timedelta values in ForecastingHorizon (#2333) @khrapovs

  • [ENH] probabilistic methods for ColumnEnsembleForecaster (except predict_proba) (#2356) @fkiraly

  • [ENH] NaiveVariance: verbose arg and extended docstring (#2395) @fkiraly

  • [ENH] Grid search with probabilistic metrics (#2234) @eenticott-shell

  • [ENH] wrapper for stream forecasting (update_predict use) to trigger regular refit (#2305) @fkiraly

  • [ENH] post-processing in TransformedTargetForecaster, dunder method for (transformed y) forecasting pipelines (#2404) @fkiraly

  • [ENH] suppressing deprecation messages in all_estimators estimator retrieval, address dtw import message (#2418) @katiebuc

  • [ENH] improved error message in forecasters when receiving an incompatible input (#2314) @fkiraly

  • [ENH] NaiveVariance: verbose arg and extended docstring (#2395) @fkiraly

  • [ENH] Prohibit incompatible splitter parameters (#2328) @khrapovs

  • [ENH] added interface to statsmodels SARIMAX (#2400) @TNTran92

  • [ENH] extending reducers to hierarchical data, adding transformation (#2396) @danbartl

Time series classification#

  • [ENH] Faster classifier example parameters (#2378) @MatthewMiddlehurst

  • [ENH] BaseObject.is_composite utility, relax errors in BaseClassifier input checks to warnings for composites (#2366) @fkiraly

  • [ENH] Capability inference for transformer and classifier pipelines (#2367) @fkiraly

Transformations#

  • [ENH] Implement reconcilers for hierarchical predictions - transformers (#2287) @ciaran-g

  • [ENH] Hierarchy aggregation transformer (#2292) @ciaran-g

  • [ENH] memory for WindowSummarizer to enable transform windows to reach into the fit time period (#2325) @fkiraly

Maintenance#

  • [MNT] Remove jinja2 version (#2330) @aiwalter

  • [ENH] test generation error to raise and not return (#2298) @fkiraly

  • [ENH] Remove pd.Int64Index due to impending deprecation (#2339, #2390) @khrapovs

  • [MNT] removing unused imports from tests._config (#2358) @fkiraly

  • [ENH] scenarios for hierarchical forecasting and tests for probabilistic forecast methods (#2359) @fkiraly

  • [MNT] fixing click/black incompatibility in CI (#2353, #2372) @fkiraly

  • [ENH] tests for check_estimator` tests passing (#2408) @fkiraly

  • [ENH] Fix tests to prevent guaranteed check_estimator failure (#2405) @danbartl

Refactored#

  • [ENH] remove non-compliant fit_params kwargs throughout the code base (#2343) @fkiraly

  • [ENH] Classification expected output test updates (#2295) @MatthewMiddlehurst

  • [ENH] Transformers module full refactor - part III, panel module (2nd batch) (#2253) @fkiraly

  • [ENH] Transformers module full refactor - part IV, panel module (3rd batch) (#2369) @fkiraly

  • [ENH] test parameter refactor: TSInterpolator (#2342) @NoaBenAmi

  • [ENH] move “sktime forecaster tests” into TestAllForecasters class (#2311) @fkiraly

  • [ENH] upgrade BasePairwiseTransformer to use datatypes input conversions and checks (#2363) @fkiraly

  • [ENH] extend _HeterogeneousMetaEstimator estimator to allow mixed tuple/estimator list (#2406) @fkiraly

  • [MNT] test parameter refactor: forecasting reducers and ColumnEnsembleClassifier (#2223) @fkiraly

  • [ENH] refactoring test_all_transformers to test class architecture (#2252) @fkiraly

Fixes#

Forecasting#

  • [BUG] fix _update default for late fh pass case (#2362) @fkiraly

  • [ENH] Extract cached ForecastingHorizon methods to functions and avoid B019 error (#2364) @khrapovs

  • [ENH] AutoETS prediction intervals simplification (#2320) @fkiraly

  • [BUG] fixed get_time_index for most mtypes (#2380) @fkiraly

Transformations#

  • [BUG] TSInterpolator and nested_univ check fix (#2259) @fkiraly

  • [BUG][ENH] WindowSummarizer offset fix, easier lag specification (#2316) @danbartl

  • [BUG] FeatureUnion output column names fixed (#2324) @fkiraly

  • [ENH][BUG] fixes and implementations of missing inverse_transform in transformer compositions (#2322) @fkiraly

Documentation#

  • [DOC] fix 0.11.0 release note highlights formatting (#2310) @fkiraly

  • [DOC] typo fix contsructor -> constructor in extension templates (#2348) @fkiraly

  • [DPC] fixed the issue with 'docs/source/developer_guide/testing_framework.rst' (#2335) @0saurabh0

  • [DOC] Updated conda installation instructions (#2365) @RISHIKESHAVAN

  • [DOC] updated extension templates: link to docs and reference to check_estimator (#2303) @fkiraly

  • [DOC] Improved docstrings in forecasters (#2314) @fkiraly

  • [DOC] Added docstring examples to load data functions (#2393) @aiwalter

  • [DOC] Added platform badge to README (#2398) @aiwalter

  • [DOC] Add GSoC 2022 landing page and announcement (#2373) @lmmentel

  • [DOC] In interval_based_classification example notebook, use multivariate dataset for the multivariate examples (#1822) @ksachdeva

Contributors#

@0saurabh0, @aiwalter, @ciaran-g, @danbartl, @eenticott-shell, @fkiraly, @katiebuc, @khrapovs, @ksachdeva, @lmmentel, @ltsaprounis, @MatthewMiddlehurst, @NoaBenAmi, @RISHIKESHAVAN, @TNTran92

Version 0.11.0 - 2022-03-26#

Highlights#

  • multivariate forecasting, probabilistic forecasting section in forecasting tutorial (#2041) @kejsitake

  • hierarchical & global forecasting: forecaster and transformer interfaces are now compatible with hierarchical data, automatically vectorize over hierarchy levels (#2110, #2115, #2219) @danbartl @fkiraly

  • probabilistic forecasting: predict_var (variance forecast) and predict_proba (full distribution forecast) interfaces; performance metrics for interval and quantile forecasts (#2100, #2130, #2232) @eenticott-shell @fkiraly @kejsitake

  • dunder methods for transformer and classifier pipelines: write my_trafo1 * my_trafo2 for pipeline, my_trafo1 + my_trafo2 for FeatureUnion (#2090, #2251) @fkiraly

  • Frequently requested: AutoARIMA from statsforecast package available as StatsforecastAutoARIMA (#2251) @FedericoGarza

  • for extenders: detailed “creating sktime compatible estimator” guide

  • for extenders: simplified extension templates for forecasters and transformers (#2161) @fkiraly

Dependency changes#

  • sktime has a new optional dependency set for deep learning, consisting of tensorflow and tensorflow-probability

  • new soft dependency: tslearn (required for tslearn clusterers)

  • new soft dependency: statsforecast (required for StatsforecastAutoARIMA)

Core interface changes#

Data types, checks, conversions#

  • new Hierarchical scientific type for hierarchical time series data, with mtype format pd_multiindex_hier (row-multiindexed series)

  • new Table scientific type for “ordinary” tabular (2D data frame like) data which is not time series or sequential

  • multiple mtype formats for the Table scientific type: numpy1D, numpy2D, pd_DataFrame_Table, pd_Series_Table, list_of_dict

  • new Proba scientific type for distributions and distribution like objects (used in probabilistic forecasting)

Forecasting#

  • forecasters now also accept inputs of Panel type (panel and global forecasters) and Hierarchical type (hierarchical forecasters)

  • when a forecaster is given Panel or Hierarchical input, and only Series logic is defined, the forecaster will automatically loop over (series) instances

  • when a forecaster is given Hierarchical input, and only Panel or Series logic is defined, the forecaster will automatically loop over (panel) instances

  • new probabilistic forecasting interface for probabilistic forecasts:

    • new method predict_var(fh, X, cov=False) for variance forecasts, returns time series of predictive variances

    • new method predict_proba(fh, X, marginal=True) for distribution forecasts, returns tensorflow Distribution

Time series classification#

  • dunder method for pipelining classifier and transformers: my_trafo1 * my_trafo2 * my_clf will create a ClassifierPipeline (sklearn compatible)

Transformations#

  • transformers now also accept inputs of Panel type (panel and global transformers) and Hierarchical type (hierarchical transformers)

  • when a transformer is given Panel or Hierarchical input, and only Series logic is defined, the transformer will automatically loop over (series) instances

  • when a transformer is given Hierarchical input, and only Panel or Series logic is defined, the transformer will automatically loop over (panel) instances

  • Table scientific type is used as output of transformers returning “primitives”

  • dunder method for pipelining transformers: my_trafo1 * my_trafo2 * my_trafo3 will create a (single) TransformerPipeline (sklearn compatible)

  • dunder method for FeatureUnion of transformers: my_trafo1 + my_trafo2 + my_trafo3 will create a (single) FeatureUnion (sklearn compatible)

  • transformer dunder pipeline is compatible with sklearn transformers, automatically wrapped in a TabularToSeriesAdaptor

Deprecations and removals#

Data types, checks, conversions#

Forecasting#

  • removed: return_pred_int argument in forecaster predict, fit_predict, update_predict_single. Replaced by predict_interval and predict_quantiles interface.

  • deprecated: fit-in-predict tag is deprecated and renamed to fit_is_empty. Old tag fit-in-predict can be used until 0.12.0 when it will be removed.

  • deprecated: forecasting metrics symmetric argument default will be changed to False in 0.12.0. Until then the default is True.

Transformations#

  • removed: series transformers no longer accept a Z argument - use first argument X instead (#1365, #1730)

  • deprecated: fit-in-transform tag is deprecated and renamed to fit_is_empty. Old tag fit-in-transform can be used until 0.12.0 when it will be removed.

  • deprecated: old location in series_as_features of FeatureUnion, has moved to transformations.compose. Old location is still importable from until 0.12.0.

  • deprecated: preserve_dataframe argument of FeatureUnion, will be removed in 0.12.0.

  • deprecated: old location in transformations.series.windows_summarizer of WindowSumamrizer, has moved to transformations.series.summarize. Old location is still importable from until 0.12.0.

Enhancements#

Data types, checks, conversions#

  • [ENH] cutoff getter for Series, Panel, and Hierarchical mtypes (#2115) @fkiraly

  • [ENH] Gettimeindex to access index of hierarchical data (#2110) @danbartl

  • [ENH] datatypes support for interval and quantile based probabilistic predictions (#2130) @fkiraly

  • [ENH] sklearn typing util (#2208) @fkiraly

  • [ENH] Relaxing pd-multiindex mtype to allow string instance index (#2262) @fkiraly

Data sets and data loaders#

Clustering#

  • [ENH] tslearn added as soft dependency and used to add new clusterers. (#2048) @chrisholder

  • [ENH] Add user option to determine return type in single problem clustering/classification problems (#2139) @TonyBagnall

Distances, kernels#

  • [ENH] minor changes to Lcss distance (#2119) @TonyBagnall

  • [ENH] factory to add 3D capability to all distances exported by distances module (#2051) @fkiraly

Forecasting#

Time series classification#

Transformations#

  • [ENH] Univariate time series bootstrapping (#2065) @ltsaprounis

  • [ENH] changed FunctionTransformer._fit to common signature (#2205) @fkiraly

  • [ENH] Upgrade of BaseTransformer to use vectorization utility, hierarchical mtype compatibility (#2219) @fkiraly

  • [ENH] WindowSummarizer to deal with hierarchical data (#2154) @danbartl

  • [ENH] Transformer pipeline and dunder method (#2090) @fkiraly

  • [ENH] Tabular transformer adaptor “fit in transform” parameter (#2209) @fkiraly

  • [ENH] dunder pipelines sklearn estimator support (#2210) @fkiraly

Testing framework#

Governance#

Fixed#

  • [BUG] fixed state change caused by ThetaForecaster.predict_quantiles (#2108) @fkiraly

  • [BUG] _make_hierachical is renamed to _make_hierarchical (typo/bug) issue #2195 (#2196) @Vasudeva-bit

  • [BUG] fix wrong output type of PaddingTransformer._transform (#2217) @fkiraly

  • [BUG] fixing nested_dataframe_has_nans (#2216) @fkiraly

  • [BUG] Testing vectorization for forecasters, plus various bugfixes (#2188) @fkiraly

  • [BUG] fixed ignores-exogeneous-X tag for forecasting reducers (#2230) @fkiraly

  • [BUG] fixing STLBootstrapTransformer error message and docstrings (#2260) @fkiraly

  • [BUG] fix conversion interval->quantiles in BaseForecaster, and fix ARIMA.predict_interval (#2281) @fkiraly

  • [DOC] fix broken link to CoC (#2104) @mikofski

  • [BUG] Fix windows bug with index freq in VectorizedDF.__getitem__ (#2279) @ltsaprounis

  • [BUG] fixes duplication of Returns section in _predict_var docstring (#2306) @fkiraly

  • [BUG] Fixed bug with check_pdmultiindex_panel (#2092) @danbartl

  • [BUG] Fixed crash of kmeans, medoids when empty clusters are generated (#2060) @chrisholder

  • [BUG] Same cutoff typo-fix (#2193) @cdahlin

  • [BUG] Addressing doc build issue due to failed soft dependency imports (#2170) @fkiraly

  • Deprecation handling: sklearn 1.2 deprecation warnings (#2190) @hmtbgc

  • Deprecation handling: Replacing normalize by use of StandardScaler (#2167) @KishenSharma6

Documentation#

  • [DOC] forecaster tutorial: multivariate forecasting, probabilistic forecasting (#2041) @kejsitake

  • [DOC] New estimator implementation guide (#2186) @fkiraly

  • [DOC] simplified extension templates for transformers and forecasters (#2161) @fkiraly

  • [DOC] contributing page: concrete initial steps (#2227) @fkiraly

  • [DOC] adding “troubleshooting” link in sktime installation instructions (#2121) @eenticott-shell

  • [DOC] enhance distance doc strings (#2122) @TonyBagnall

  • [DOC] updated soft dependency docs with two tier check (#2182) @fkiraly

  • [DOC] replace gitter mentions by appropriate links, references (#2187) @TonyBagnall

  • [DOC] updated the environments doc with python version for sktime, added python 3.9 (#2199) @Vasudeva-bit

  • [DOC] Replaced youtube link with recent PyData Global (#2191) @aiwalter

  • [DOC] extended & cleaned docs on dependency handling (#2189) @fkiraly

  • [DOC] migrating mentoring form to sktime google docs (#2222) @fkiraly

  • [DOC] add scitype/mtype register pointers to docstrings in datatypes (#2160) @fkiraly

  • [DOC] improved docstrings for HIVE-COTE v1.0 (#2239) @TonyBagnall

  • [DOC] typo fix and minor clarification in estimator implementation guide (#2241) @fkiraly

  • [DOC] numpydoc compliance fix of simple forecasting extension template (#2284) @fkiraly

  • [DOC] typos in developer_guide.rst (#2131) @theanorak

  • [DOC] fix broken link to CoC (#2104) @mikofski

  • [DOC] minor update to tutorials (#2114) @ciaran-g

  • [DOC] various minor doc issues (#2168) @aiwalter

Maintenance#

  • [MNT] Update release drafter (#2096) @lmmentel

  • speed up EE tests and ColumnEnsemble example (#2124) @TonyBagnall

  • [MNT] add xfails in test_plotting until #2066 is resolved (#2144) @fkiraly

  • [MNT] add skips to entirety of test_plotting until #2066 is resolved (#2147) @fkiraly

  • [ENH] improved deep_equals return message if dict`s are discrepant (:pr:`2107) @fkiraly

  • [BUG] Addressing doc build issue due to failed soft dependency imports (#2170) @fkiraly

  • [ENH] extending deep_equals for ForecastingHorizon (#2225) @fkiraly

  • [ENH] unit tests for deep_equals utility (#2226) @fkiraly

  • [MNT] Faster docstring examples - ForecastingGridSearchCV, MultiplexForecaster (#2229) @fkiraly

  • [BUG] remove test for StratifiedGroupKFold (#2244) @TonyBagnall

  • [ENH] Classifier type hints (#2246) @MatthewMiddlehurst

  • Updated pre-commit link and also grammatically updated Coding Style docs (#2285) @Tomiiwa

  • Update .all-contributorsrc (#2286) @Tomiiwa

  • [ENH] Mock estimators and mock estimator generators for testing (#2197) @ltsaprounis

  • [MNT] Deprecation removal 0.11.0 (#2271) @fkiraly

  • [BUG] fixing pyproject and jinja2 CI failures (#2299) @fkiraly

  • [DOC] Update PULL_REQUEST_TEMPLATE.md so PRs should start with [ENH], [DOC] or [BUG] in title (#2293) @aiwalter

  • [MNT] add skips in test_plotting until #2066 is resolved (#2146) @fkiraly

Refactored#

Contributors#

@aiwalter, @cdahlin, @chrisholder, @ciaran-g, @danbartl, @dionysisbacchus, @eenticott-shell, @FedericoGarza, @fkiraly, @hmtbgc, @IlyasMoutawwakil, @kejsitake, @KishenSharma6, @lielleravid, @lmmentel, @ltsaprounis, @MatthewMiddlehurst, @mikofski, @RafaAyGar, @theanorak, @Tomiiwa, @TonyBagnall, @Vasudeva-bit,

[0.10.1] - 2022-02-20#

Highlights#

  • This release is mainly a maintenance patch which upper bounds scipy<1.8.0 to prevent bugs due to interface changes in scipy.

  • Once sktime is compatible with scipy 1.8.0, the upper bound will be relaxed

  • New forecaster: STLForecaster (#1963) @aiwalter

  • New transformer: lagged window summarizer transformation (#1924) @danbartl

  • Loaders for .tsf data format (#1934) @rakshitha123

Dependency changes#

  • Introduction of bound scipy<1.8.0, to prevent bugs due to interface changes in scipy

  • Once sktime is compatible with scipy 1.8.0, the upper bound will be relaxed

Added#

Documentation#

Data sets and data loaders#

Data types, checks, conversions#

  • [ENH] convert store reset/freeze behaviour & fix of bug 1976 (#1977) @fkiraly

  • [ENH] new Table mtypes: pd.Series based, list of dict (as used in bag of words transformers) (#2076) @fkiraly`

Forecasting#

  • [ENH] Added STLForecaster (#1963) @aiwalter

  • [ENH] moving forecaster test params from _config into classes - all forecasters excluding reduction (#1902) @fkiraly

Transformations#

Maintenance#

Fixed#

Contributors#

@aiwalter, @baggiponte, @chicken-biryani, @danbartl, @eenticott-shell, @fkiraly, @khrapovs, @lmmentel, @MatthewMiddlehurst, @rakshitha123, @RishiKumarRay, @Rubiel1, @Saransh-cpp, @schettino72,

[0.10.0] - 2022-02-02#

Highlights#

Dependency changes#

  • sktime now supports python 3.7-3.9 on windows, mac, and unix-based systems

  • sktime now supports, and requires, numpy>=1.21.0 and statsmodels>=0.12.1

  • sktime Prophet interface now uses prophet instead of deprecated fbprophet

  • developer install for sktime no longer requires C compilers and cython

Core interface changes#

Forecasting#

New probabilistic forecasting interface for quantiles and predictive intervals:

  • for all forecasters with probabilistic forecasting capability, i.e., capability:pred_int tag

  • new method predict_interval(fh, X, coverage) for interval forecasts

  • new method predict_quantiles(fh, X, alpha) for quantile forecasts

  • both vectorized in coverage, alpha and applicable to multivariate forecasting

  • old return_pred_int interface is deprecated and will be removed in 0.11.0

  • see forecaster base API and forecaster extension template

Convenience method to return residuals:

  • all forecasters now have a method predict_residuals(y, X, fh)

  • if fh is not passed, in-sample residuals are computed

Transformations#

Base interface refactor rolled out to series transformers (#1790, #1795):

  • fit, transform, fit_transform now accept both Series and Panel as argument

  • if Panel is passed to a series transformer, it is applied to all instances

  • all transformers now have signature transform(X, y=None) and inverse_transform(X, y=None). This is enforced by the new base interface.

  • Z (former first argument) aliases X until 0.11.0 in series transformers, will then be removed

  • X (former second argument) was not used in those transformers, was changed to y

  • see transformer base API and transformer extension template

Deprecations and removals#

Data types, checks, conversions#

  • deprecated, scheduled for removal in 0.11.0: check_is renamed to check_is_mtype, check_is to be removed in 0.11.0 (#1692) @mloning

Forecasting#

  • deprecated, scheduled for removal in 0.11.0: return_pred_int argument in forecaster predict, fit_predict, update_predict_single. Replaced by predict_interval and predict_quantiles interface.

Time series classification#

Transformations#

  • deprecated, scheduled for removal in 0.11.0: series transformers will no longer accept a Z argument - first argument Z replaced by X (#1365, #1730)

Added#

Documentation#

Data types, checks, conversions#

  • [ENH] check_is_scitype, cleaning up dists_kernels input checks/conversions (#1704) @fkiraly

  • [ENH] Table scitype and refactor of convert module (#1745) @fkiraly

  • [ENH] estimator scitype utility (#1838) @fkiraly

  • [ENH] experimental: hierarchical time series scitype hierarchical_scitype (#1786) @fkiraly

  • [ENH] upgraded mtype_to_scitype to list-like args (#1807) @fkiraly

  • [ENH] check_is_mtype to return scitype (#1789) @fkiraly

  • [ENH] vectorization/iteration utility for sktime time series formats (#1806) @fkiraly

Data sets and data loaders#

Clustering#

Distances, kernels#

  • [ENH] Composable distances interface prototype for numba distance module (#1858) @fkiraly

Forecasting#

  • [ENH] Scaled Logit Transformer (#1913, #1965) @ltsaprounis.

  • [ENH] add fit parameters to statsmodels Holt-Winters exponential smoothing interface (#1849) @fkiraly

  • [ENH] Add predict_quantiles to FBprophet (#1910) @kejsitake

  • [ENH] Add `predict_quantiles to ets, pmdarima adapter (#1874) @kejsitake

  • [ENH] Defaults for _predict_interval and _predict_coverage (#1879, #1961) @fkiraly

  • [ENH] refactored column ensemble forecaster (#1764) @Aparna-Sakshi

  • [ENH] Forecaster convenience method to return forecast residuals (#1770) @fkiraly

  • [ENH] Update extension template for predict_quantiles (#1780) @kejsitake

  • [ENH] Prediction intervals refactor: BATS/TBATS; bugfix for #1625; base class updates on predict_quantiles (#1842) @k1m190r

  • [ENH] Change _set_fh to a _check_fh that returns self._fh (#1823) @fkiraly

  • [ENH] Generalize splitters to accept timedeltas (equally spaced) (#1758) @khrapovs

Time series classification#

Transformations#

  • [ENH] Transformers module full refactor - part I, series module (#1795) @fkiraly

  • [ENH] Transformer base class DRY-ing, and inverse_transform (#1790) @fkiraly

  • [ENH] transformer base class to allow multivariate output if input is always univariate (#1706) @fkiraly

Testing module#

  • [ENH] Test refactor with scenarios (#1833) @fkiraly

  • [ENH] Test scenarios for advanced testing (#1819) @fkiraly

  • [ENH] pytest conditional fixtures (#1839) @fkiraly

  • [ENH] Test enhacements documentation (#1922) @fkiraly

  • [ENH] split tests in series_as_features into classification and regression (#1959) @tonybagnall

  • [ENH] Testing for metadata returns of check_is_mtype (#1748) @fkiraly

  • [ENH] Extended deep_equals, with precise indication of why equality fails (#1844) @fkiraly

  • [ENH] test for test_create_test_instances_and_names fixture generation method (#1829) @fkiraly

  • [ENH] Utils module housekeeping varia utils-housekeeping (#1820) @fkiraly

  • [ENH] Extend testing framework to test multiple instance fixtures per estimator (#1732) @fkiraly

Governance#

Maintenance#

  • [MNT] Switch the extra dependency from fbprophet to prophet (#1958) @lmmentel

  • [MNT] Updated code dependency version, i.e. numpy and statsmodels to reduce dependency conflicts (#1921) @lmmentel

  • [MNT] Move all the CI/CD worfklows over to github actions and drop azure pipelines and appveyor (#1620, #1920) @lmemntel

  • [MNT] Refactor legacy test config (#1792) @lmmentel

  • [FIX] Add missing init files (#1695) @mloning

  • [MNT] Add shellcheck to pre-commit (#1703) @mloning

  • [MNT] Remove assign-contributor workflow (#1702) @mloning

  • [MNT] Fail CI on missing init files (#1699) @mloning

  • [ENH] replace deprecated np.int, np.float (#1734) @fkiraly

  • [MNT] Correct the bash error propagation for running notebook examples (#1816) @lmmentel

Fixed#

  • [DOC] Fixed a typo in transformer extension template (#1901) @rakshitha123

  • [DOC] Fix typo in Setting up a development environment section (#1872) @shubhamkarande13

  • [BUG] Fix incorrect “uses X” tag for ARIMA and TrendForecaster (#1895) @ngupta23

  • [BUG] fix error when concatenating train and test (#1892) @tonybagnall

  • [BUG] Knn bugfix to allow GridsearchCV and usage with column ensemble (#1903) @tonybagnall

  • [BUG] Fixes various bugs in DrCIF, STSF, MUSE, Catch22 (#1869) @MatthewMiddlehurst

  • [BUG] fixing mixup of internal variables in detrender (#1863) @fkiraly

  • [BUG] transformer base class changes and bugfixes (#1855) @fkiraly

  • [BUG] fixed erroneous index coercion in convert_align_to_align_loc (#1911) @fkiraly

  • [BUG] bugfixes for various bugs discovered in scenario testing (#1846) @fkiraly

  • [BUG] 1523 fixing ForecastHorizon.to_absolute for freqs with anchorings (#1830) @eenticott-shell

  • [BUG] remove duplicated input checks from BaseClassifier.score (#1813) @fkiraly

  • [BUG] fixed mtype return field in check_is_scitype (#1805) @fkiraly

  • [BUG] fix fh -> self.fh in predict_interval and predict_quantiles (#1775) @fkiraly

  • [BUG] fix incorrect docstrings and resolving confusion unequal length/spaced in panel metadata inference (#1768) @fkiraly

  • [BUG] hotfix for bug when passing multivariate y to boxcox transformer (#1724) @fkiraly

  • [BUG] fixes CIF breaking with CIT, added preventative test (#1709) @MatthewMiddlehurst

  • [BUG] Correct the examples/catch22.ipynb call to transform_single_feature (#1793) @lmmentel

  • [BUG] Fixes prophet bug concerning the internal change of exogenous X (#1711) @kejsitake

  • [BUG] Fix DeprecationWarning of pd.Series in sktime/utils/tests/test_datetime.py:21 (#1743) @khrapovs

  • [BUG] bugfixes in BaseClassifier, updated base class docstrings (#1804) @fkiraly

Contributors#

@aiwalter, @amrith-shell, @Aparna-Sakshi, @AreloTanoh, @chrisholder, @eenticott-shell, @fkiraly, @k1m190r, @kejsitake, @khrapovs, @lmmentel, @ltsaprounis, @MatthewMiddlehurst, @MrPr3ntice, @mloning, @ngupta23, @rakshitha123, @RNKuhns, @shubhamkarande13, @sumit-158, @TonyBagnall,

[0.9.0] - 2021-12-08#

Highlights#

  • frequently requested: AutoARIMA get_fitted_params access for fitted order and seasonal order (#1641) @AngelPone

  • Numba distance module - efficient time series distances (#1574) @chrisholder

  • Transformers base interface refactor - default vectorization to panel data @fkiraly

  • new experimental module: Time series alignment, dtw-python interface (#1264) @fkiraly

Core interface changes#

Data types, checks, conversions#

  • check_is renamed to check_is_mtype, check_is to be deprecated in 0.10.0 (#1692) @mloning

Time series classification#

  • time series classifiers now accept 2D np.ndarray by conversion to 3D rather than throwing exception (#1604) @TonyBagnall

Transformations#

Base interface refactor (#1365, #1663, #1706):

  • fit, transform, fit_transform now accept both Series and Panel as argument

  • if Panel is passed to a series transformer, it is applied to all instances

  • all transformers now use X as their first argument, y as their second argument. This is enforced by the new base interface.

  • This was inconsistent previously between types of transformers: the series-to-series transformers were using Z as first argument, X as second argument.

  • Z (former first argument) aliases X until 0.10.0 in series transformers, will then be deprecated

  • X (former second argument) was not used in those transformers where it changed to y

  • see new transformer extension template

  • these changes will gradually be rolled out to all transformers through 0.9.X versions

New deprecations for 0.10.0#

Data types, checks, conversions#

  • check_is renamed to check_is_mtype, check_is to be deprecated in 0.10.0 (#1692) @mloning

Time series classification#

Transformations#

  • series transformers will no longer accept a Z argument - first argument Z replaced by X (#1365)

Added#

Documentation#

Data types, checks, conversions#

  • [ENH] added check_is_scitype for scitype checks, cleaning up dists_kernels input checks/conversions (#1704) @fkiraly

Forecasting#

  • [ENH] Auto-ETS checks models to select from based on non-negativity of data (#1615) @chernika158

  • [DOC] meta-tuning examples for docstring of ForecastingGridSearchCV (#1656) @aiwalter

Time series alignment#

  • [ENH] new module: time series alignment; alignment distances (#1264) @fkiraly

Time series classification#

Time series distances#

Governance#

Maintenance#

Fixed#

Estimator registry#

  • [BUG] Fixes to registry look-up, test suite for registry look-up (#1648) @fkiraly

Forecasting#

  • [BUG] Facebook prophet side effects on exogenous data X (#1711) @kejsitake

  • [BUG] fixing bug for _split, accidental removal of pandas.Index support (#1582) @fkiraly

  • [BUG] Fix convert and _split for Numpy 1D input (#1650) @fkiraly

  • [BUG] issue with update_y_X when we refit forecaster by (#1595) @ltsaprounis

Performance metrics, evaluation#

Time series alignment#

Time series classification#

Transformations#

Maintenance#

Contributors#

@aiwalter, @AngelPone, @AreloTanoh, @Carlosbogo, @chernika158, @chrisholder, @fstinner, @fkiraly, @freddyaboulton, @kejsitake, @lmmentel, @ltsaprounis, @MatthewMiddlehurst, @marcio55afr, @MrPr3ntice, @mloning, @OliverMatthews, @RNKuhns, @thayeylolu, @TonyBagnall,

Full changelog#

https://github.com/alan-turing-institute/sktime/compare/v0.8.1…v0.9.0

[0.8.1] - 2021-10-28#

Highlights#

New deprecations for 0.10.0#

Forecasting#

  • current prediction intervals interface in predict via return_pred_int will be deprecated and replaced by the new interface points predict_interval and predict_quantiles

Core interface changes#

Forecasting#

  • new interface points for probabilistic forecasting, predict_interval and predict_quantiles (#1421) @SveaMeyer13

  • changed forecasting univariate-only tag to ignores-exogeneous-X (#1358) @fkiraly

Added#

BaseEstimator/BaseObject#

Forecasting#

Time series classification#

Transformers#

Annotation: change-points, segmentation#

  • Clasp for time series segmentation (CIKM’21 publication) (#1352) @patrickzib

Documentation#

Governance#

Testing framework#

  • Tests refactor: using pytest_generate_tests instead of loops (#1407) @fkiraly

  • Tests refactor: Adding get_test_params method to extension template (#1395) @Aparna-Sakshi

  • Changed defaults in make_forecasting_problem (#1477) @aiwalter

Fixed#

All contributors: @Aparna-Sakshi, @BINAYKUMAR943, @IlyasMoutawwakil, @MatthewMiddlehurst, @Piyush1729, @RNKuhns, @RavenRudi, @SveaMeyer13, @TonyBagnall, @afzal442, @aiwalter, @bobbys-dev, @boukepostma, @danbartl, @eyalshafran, @fkiraly, @freddyaboulton, @kejsitake, @mloning, @myprogrammerpersonality, @patrickzib, @ronnie-llamado, @xiaobenbenecho, @SinghShreya05, and @yairbeer

[0.8.0] - 2021-09-17#

Highlights#

Core interface changes#

BaseEstimator/BaseObject#

  • estimator (class and object) capabilities are inspectable by get_tag and get_tags interface

  • list all tags applying to an estimator type by registry/all_tags

  • list all estimators of a specific type, with certain tags, by registry/all_estimators

In-memory data types#

  • introduction of m(achine)types and scitypes for defining in-memory format conventions across all modules, see in-memory data types tutorial

  • loose conversion methods now in _convert files in datatypes will no longer be publicly accessible in 0.10.0

Forecasting#

  • Forecasters can now be passed pd.DataFrame, pd.Series, np.ndarray as X or y, and return forecasts of the same type as passed for y

  • sktime now supports multivariate forecasters, with all core interface methods returning sensible return types in that case

  • whether forecaster can deal with multivariate series can be inspected via get_tag("scitype:y"), which can return "univariate", "multivariate", or "both"

  • further tags have been introduced, see registry/all_tags

Time series classification#

  • tags have been introduced, see registry/all_tags

Added#

Forecasting#

Time series classification#

Transformers#

Benchmarking and evaluation#

Documentation#

Testing framework#

  • unit test for absence of side effects in estimator methods (#1078) @fkiraly

Fixed#

All contributors: @Aparna-Sakshi, @AreloTanoh, @BINAYKUMAR943, @Flix6x, @GuzalBulatova, @IlyasMoutawwakil, @Lovkush-A, @MatthewMiddlehurst, @RNKuhns, @SveaMeyer13, @TonyBagnall, @afzal442, @aiwalter, @bilal-196, @corvusrabus, @fkiraly, @freddyaboulton, @juanitorduz, @justinshenk, @ltoniazzi, @mathco-wf, @mloning, @moradabaz, @pul95, @tensorflow-as-tf, @thayeylolu, @victordremov, @whackteachers and @xloem

[0.7.0] - 2021-07-12#

Added#

Changed#

Fixed#

All contributors: @Dbhasin1, @GuzalBulatova, @Lovkush-A, @MarcoGorelli, @MatthewMiddlehurst, @RNKuhns, @Riyabelle25, @SveaMeyer13, @TonyBagnall, @Yard1, @aiwalter, @chrisholder, @ckastner, @fkiraly, @jambo6, @julramos, @kachayev, @ltsaprounis, @mloning, @thayeylolu and @tombh

[0.6.1] - 2021-05-14#

Fixed#

Changed#

Added#

All contributors: @GuzalBulatova, @RNKuhns, @aaronreidsmith, @aiwalter, @kachayev, @ltsaprounis, @luiszugasti, @mloning, @satya-pattnaik and @yashlamba

[0.6.0] - 2021-04-15#

Fixed#

Changed#

Added#

All contributors: @AidenRushbrooke, @Ifeanyi30, @Lovkush-A, @MarcoGorelli, @MatthewMiddlehurst, @TonyBagnall, @afzal442, @aiwalter, @ayan-biswas0412, @dsherry, @jschemm, @kanand77, @koralturkk, @luiszugasti, @mloning, @pabworks and @xuyxu

[0.5.3] - 2021-02-06#

Fixed#

Changed#

Added#

All contributors: @Lovkush-A, @MatthewMiddlehurst, @RNKuhns, @TonyBagnall, @ViktorKaz, @aiwalter, @goastler, @koralturkk, @mloning, @pabworks, @patrickzib and @xuyxu

[0.5.2] - 2021-01-13#

Fixed#

All contributors: @Hephaest, @MatthewMiddlehurst, @TonyBagnall, @aiwalter and @dhirschfeld

[0.5.1] - 2020-12-29#

Added#

Fixed#

  • Pin pandas version to fix pandas-related AutoETS error on Linux (#581) @mloning

  • Fixed default argument in docstring in SlidingWindowSplitter (#556) @ngupta23

All contributors: @HYang1996, @TonyBagnall, @afzal442, @aiwalter, @angus924, @juanitorduz, @mloning and @ngupta23

[0.5.0] - 2020-12-19#

Added#

Changed#

Fixed#

Removed#

All contributors: @AaronX121, @Afzal-Ind, @AidenRushbrooke, @HYang1996, @MarcoGorelli, @MatthewMiddlehurst, @MichalChromcak, @TonyBagnall, @aiwalter, @bmurdata, @davidbp, @gracewgao, @magittan, @mloning, @ngupta23, @patrickzib, @raishubham1, @tch, @utsavcoding, @vnmabus, @vollmersj and @whackteachers

[0.4.3] - 2020-10-20#

Added#

Changed#

Fixed#

All contributors: @Emiliathewolf, @alwinw, @evanmiller29, @kkoziara, @krumeto, @mloning and @patrickzib

[0.4.2] - 2020-10-01#

Added#

Fixed#

Changed#

  • Move documentation to ReadTheDocs with support for versioned documentation (#395) @mloning

  • Refactored SFA implementation (additional features and speed improvements) (#389) @patrickzib

  • Move prediction interval API to base classes in forecasting framework (#387) @big-o

  • Documentation improvements (#364) @mloning

  • Update CI and maintenance tools (#394) @mloning

All contributors: @HYang1996, @SebasKoel, @fkiraly, @akanz1, @alwinw, @big-o, @brettkoonce, @mloning, @patrickzib

[0.4.1] - 2020-07-09#

Added#

Changed#

Fixed#

All contributors: @Ayushmaanseth, @Mo-Saif, @Pangoraw, @marielledado, @mloning, @sophijka, @Cheukting, @MatthewMiddlehurst, @Multivin12, @ABostrom, @HYang1996, @BandaSaiTejaReddy, @vedazeren, @hiqbal2, @btrtts

[0.4.0] - 2020-06-05#

Added#

  • Forecasting framework, including: forecasting algorithms (forecasters), tools for composite model building (meta-forecasters), tuning and model evaluation

  • Consistent unit testing of all estimators

  • Consistent input checks

  • Enforced PEP8 linting via flake8

  • Changelog

  • Support for Python 3.8

  • Support for manylinux wheels

Changed#

  • Revised all estimators to comply with common interface and to ensure scikit-learn compatibility

Removed#

  • A few redundant classes for the series-as-features setting in favour of scikit-learn’s implementations: Pipeline and GridSearchCV

  • HomogeneousColumnEnsembleClassifier in favour of more flexible ColumnEnsembleClassifier

Fixed#

  • Deprecation and future warnings from scikit-learn

  • User warnings from statsmodels