v0.3.0¶
June 2023
Following this release the deprecation policy remains suspended. Future releases may have breaking changes, so it may be wise to set an upper bound on the package version.
Highlights¶
An interface to the MrSQM algorithm has been added to the classification module.
k-NN estimators and the Elastic Ensemble classifier now support unequal length series.
The SAX transformation has been refactored to improve performance.
A new collection transformer base class has been added to the transformations module for more efficient transformation using collections of time series.
A rework of the benchmarking module has begun, starting with the introduction of functionality from
kotsu
Benchmarking¶
Enhancements¶
[ENH] remove unsupported legacy benchmarking code (#439) @TonyBagnall
[ENH] Rework datasets package notebooks (#468) @TonyBagnall
Classification¶
Bug Fixes¶
[BUG] refactored params usage resnet (#433) @hadifawaz1999
[BUG] Ordinal TDE _n_jobs (#471) @MatthewMiddlehurst
Enhancements¶
[ENH] Parametrize model saving for deep classifiers and regressors (#430) @hadifawaz1999
[ENH] Ordinal TDE algorithm and extension of SFA transformer (#335) @RafaAyGar
[ENH] Facilitate multivariate and unequal length with ElasticEnsemble classifier (#415) @TonyBagnall
[ENH] refactor _threads_to_use to _n_jobs (#377) @TonyBagnall
[ENH] MrSQM classification wrapper (#476) @MatthewMiddlehurst
Refactored¶
[ENH] refactor _threads_to_use to _n_jobs (#377) @TonyBagnall
Other¶
[ENH] Allow KNN to take unequal length series. (#412) @TonyBagnall
Clustering¶
Bug Fixes¶
[BUG] Tslearn clusterers update (#457) @chrisholder
Distances¶
Bug Fixes¶
[BUG] KNN distance params (#447) @chrisholder
Enhancements¶
[ENH] updated dba to support custom parameters (#454) @chrisholder
Other¶
[ENH] Allow KNN to take unequal length series. (#412) @TonyBagnall
Regression¶
Enhancements¶
[ENH] Parametrize model saving for deep classifiers and regressors (#430) @hadifawaz1999
[ENH] Enable knn regressor to take unequal length (#442) @TonyBagnall
[MNT] Add deep learning regression/classification test (#443) @hadifawaz1999
Transformations¶
Bug Fixes¶
[ENH] Convert IntervalSegmenter and RandomIntervalSegmenter to use numpy3D internally (#391) @TonyBagnall
[BUG] Fixes RDST bug and small docstring changes (#475) @MatthewMiddlehurst
Enhancements¶
[ENH] Ordinal TDE algorithm and extension of SFA transformer (#335) @RafaAyGar
[ENH] Collection transformer base class (#263) @MatthewMiddlehurst
[ENH] Refactor sax (#417) @hadifawaz1999
Maintenance¶
[MNT] Rename
panel
transformers folder tocollection
(#466) @MatthewMiddlehurst
Refactored¶
[ENH] Refactor sax (#417) @hadifawaz1999
[MNT] Rename
panel
transformers folder tocollection
(#466) @MatthewMiddlehurst
Other¶
Bug Fixes¶
[BUG]
plot_series
bugfix and tests (#318) @MatthewMiddlehurst[BUG] Fixes
stratified_resample
so that it works with 3D numpy (#460) @GuiArcencio
Documentation¶
[DOC] Add to getting_started page (#393) @TonyBagnall
[DOC] README deprecation policy disclaimer (#453) @MatthewMiddlehurst
[DOC] README getting started section (#462) @MatthewMiddlehurst
[DOC] Getting started page pipeline examples (#461) @MatthewMiddlehurst
Enhancements¶
[ENH]
numba
utility functions (#465) @MatthewMiddlehurst[ENH] data loaders and writers (#463) @TonyBagnall
Maintenance¶
[MNT] Set upper bound on
holidays
to fix CI (#436) @MatthewMiddlehurst[MNT] Recursively find notebooks for testing (#470) @MatthewMiddlehurst
Other¶
[EN] Hard code deep learning exclusions from tests (#419) @TonyBagnall
[ENH] Remove the uses of the nested univariate data generator (#373) @TonyBagnall
Contributors¶
The following have contributed to this release through a collective 33 GitHub Pull Requests:
@chrisholder, @DBCerigo, @GuiArcencio, @hadifawaz1999, @MatthewMiddlehurst, @RafaAyGar, @TonyBagnall