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Releases: eonu/sequentia

v2.0.2

13 Apr 17:46
daf5d70
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What's Changed

  • release: v2.0.1 by @github-actions in #248
  • fix: call KNNMixin._dtw1d when independent=True by @eonu in #251

Full Changelog: v2.0.1...v2.0.2

v2.0.1

02 Apr 09:24
d93bab5
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What's Changed

  • release: v2.0.0 by @github-actions in #244
  • fix: use log probs for KNNClassifier.predict_log_proba by @eonu in #247

Full Changelog: v2.0.0...v2.0.1

v2.0.0

01 Apr 17:47
9fae88f
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What's Changed

  • release 1.1.1 by @eonu in #240
  • refactor: full scikit-learn compatibility + general refactor by @eonu in #241
  • docs: fix README.md logo URL by @eonu in #243

Full Changelog: v1.1.1...v2.0.0

v1.1.1

01 Feb 08:37
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Major changes

  • Remove scikit-learn validation constraints from IndependentFunctionTransformer. (#237)

Minor changes

  • Change default mean_filter/median_filter width to 5. (#238)
  • Update repository documentation. (#239)

v1.1.0

18 Jan 01:43
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Major changes

Minor changes

  • Upgrade sklearn version specifier from >=0.22 to >=1.0. (#234)
  • Upgrade development status classifier to stable. (#233)

v1.0.0

27 Dec 17:49
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Major changes

  • Fix CategoricalHMM and GaussianMixtureHMM parameter defaults for params/init_params being modified. (#231)
  • Fix CategoricalHMM and GaussianMixtureHMM unfreeze() calling super().freeze() instead of super().unfreeze(). (#231)
  • Fix serialization/deserialization for _KNNMixin when weighting=None. (#231)
  • Add unit tests. (#231)

Minor changes

  • Change load_digits numbers parameter name to digits. (#231)
  • Change SequentialDataset properties to not return copies of arrays. (#231)
  • Remove SequentialDataset.__eq__. (#231)
  • Change HMMClassifier prior default to None. (#231)

v1.0.0a2

06 Dec 22:19
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v1.0.0a2 Pre-release
Pre-release

Minor changes

  • Fix broken link on README.md. (#229)

v1.0.0a1

06 Dec 22:03
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v1.0.0a1 Pre-release
Pre-release

Major changes

  • Rework interface to follow sklearn-like patterns. (#226)
  • Remove preprocessing module (temporarily until design is finalized). (#226)
  • Add KNN regression. (#226)
  • Add HMM classifier with categorical emissions. (#226)
  • Use Pydantic for better validation. (#226)
  • Add datasets module for sample datasets. (#226)
  • Split KNN logic across more functions. (#226)
  • Better multi-processing for KNN. (#226)
  • Documentation rework + switch Sphinx documentation theme. (#226)
  • Fix Sakoe-Chiba width calculation. (#226)

v0.13.1

26 Jun 20:34
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Major changes

  • Add datasets.load_random_sequences for generating an arbitrarily sized dataset of sequences. (#216)
  • Remove DeepGRU and classifier.rnn module. (#215)
  • Add sequentia.datasets module. (#214)
  • Added return_scores argument to KNNClassifier.predict() to return class scores. (#213)
  • Return self in fit() functions. (#213)
  • Update to hmmlearn v0.2.7. (#201)
  • Update HMMClassifier structure to match KNNClassifier. (#200)
  • Remove 'uniform' KNNClassifier weighting option. (#192)
  • Fix major KNNClassifier label scoring bug - thanks @manisci. (#187)

Minor changes

  • Add digits.npz as package data in setup.py. (#221)
  • Update CONTRIBUTING.md CI instructions. (#219)
  • Switch from TravisCI to CircleCI. (#218)
  • Update HMM tests to use datasets module. (#217)
  • Add tslearn as a core dependency. (#216)
  • Remove torchaudio, torchvision and torchfsdd dependencies. (#214)
  • Add playable audio to notebooks via play_audio helper. (#214)
  • Update README.md and documentation. (#202)
  • Add Jinja2 dependency for RTD. (#188)

v0.12.1

22 Jan 13:37
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  • KNNClassifier has a major bug in all versions prior to and including v0.12.1 resulting in inaccurate predictions (see #186).

  • GMMHMM and HMMClassifier have a major bug in all versions prior to and including v0.12.1 as a result of two bugs in the GMMHMM class in hmmlearn versions before v0.2.7 (see #193).

⚠️ Please use version v0.13.0 or later.

Major changes

  • Remove requirements.py due to import error. (#182)