Releases: AlexanderFabisch/gmr
Releases · AlexanderFabisch/gmr
2.0.3
2.0.2
Documentation
- Switch to markdown format for readme
2.0.1
Maintenance
- Replace setup.py by pyproject.toml
2.0.0
1.6.1
Final version of JOSS paper
1.6
- Fixes numerical issues in condition and expectation step
- Add oracle approximating shrinkage to handle singular covariances
- Add sklearn-compatible GaussianMixtureRegressor
- Faster batch prediction of means
- Accept lists where previously only numpy arrays were accepted
1.5.1
Installation works now without any dependencies.
1.5
Installation
- Changes
requirestoinstall_requiresinsetup.py - Adds optional requirements for examples, tests, and documentation
Documentation
- Links new API documentation in readme
- Documentation in example
plot_iris_from_sklearn.pyexplains why the fit is bad. The purpose of this example is to show that we can initialize from a GMM of sklearn. - Documentation of how to contribute to the software (in readme)
Code
- Fixes deprecation warnings for NumPy type aliases
- Adds
GMM.extract_mvn
1.4
- Adds unscented transform to MVN
- Extend documentation in readme