v2.0.2

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

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

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

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

Major changes

• Set max_nbytes=None to fix read-only buffer source array error in joblib.Parallel (see scikit-learn/scikit-learn#7981). (#235)
• Added sequentia.preprocessing module with sklearn.preprocessing compatibility. (#234)
• Added sequentia.pipeline module for sklearn.pipeline compatibility. (#234)

Minor changes

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

v1.0.0

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

Minor changes

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

v1.0.0a1

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

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

• 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)