Releases: eonu/sequentia
Releases · eonu/sequentia
v2.6.0
What's Changed
- docs: fix
KNNRegressor.windowdocstring typo by @eonu in #261 - fix: enable
joblib.Parallelmemory mapping by @eonu in #262 - feat: set
use_c=Trueby default forKNNClassifier/KNNRegressorby @eonu in #263 - style: upgrade to
ruffv0.8.4 and fix type hints by @eonu in #264 - docs: update
README.mdfeatures by @eonu in #265
Full Changelog: v2.5.0...v2.6.0
v2.5.0
What's Changed
Documentation
- update copyright notice (#255)
Features
- add
mise.tomland supportnumpy>=2(#254) - add python v3.13 support (#253)
- add library benchmarks (#256)
- add
model_selectionsub-package for hyper-parameters (#257) - add model spec support to
HMMClassifier.__init__(#258) - add
HMMClassifier.fitmultiprocessing (#259)
Full Changelog: v2.0.1...v2.5.0
v2.0.2
What's Changed
- release: v2.0.1 by @github-actions in #248
- fix: call
KNNMixin._dtw1dwhenindependent=Trueby @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_probaby @eonu in #247
Full Changelog: v2.0.0...v2.0.1
v2.0.0
v1.1.1
v1.1.0
Major changes
- Set
max_nbytes=Noneto fix read-only buffer source array error injoblib.Parallel(see scikit-learn/scikit-learn#7981). (#235) - Added
sequentia.preprocessingmodule withsklearn.preprocessingcompatibility. (#234) - Added
sequentia.pipelinemodule forsklearn.pipelinecompatibility. (#234)
Minor changes
v1.0.0
Major changes
- Fix
CategoricalHMMandGaussianMixtureHMMparameter defaults forparams/init_paramsbeing modified. (#231) - Fix
CategoricalHMMandGaussianMixtureHMMunfreeze()callingsuper().freeze()instead ofsuper().unfreeze(). (#231) - Fix serialization/deserialization for
_KNNMixinwhenweighting=None. (#231) - Add unit tests. (#231)
Minor changes
v1.0.0a2
v1.0.0a1
Major changes
- Rework interface to follow sklearn-like patterns. (#226)
- Remove
preprocessingmodule (temporarily until design is finalized). (#226) - Add KNN regression. (#226)
- Add HMM classifier with categorical emissions. (#226)
- Use Pydantic for better validation. (#226)
- Add
datasetsmodule 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)