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Releases: AlexanderFabisch/gmr

2.0.3

12 Jan 08:01

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Bugfix

2.0.2

13 Aug 10:59

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Documentation

  • Switch to markdown format for readme

2.0.1

13 Aug 10:35

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Maintenance

  • Replace setup.py by pyproject.toml

2.0.0

13 Aug 10:00

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Bugfix

  • Correct scaling factor in MVN.to_norm_factor_and_exponents so that integral of probability densities is 1 (#58)

1.6.1

01 Jun 12:45

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Final version of JOSS paper

1.6

28 May 12:48

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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

14 Mar 14:22

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Installation works now without any dependencies.

1.5

13 Mar 18:06

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1.5

Installation

  • Changes requires to install_requires in setup.py
  • Adds optional requirements for examples, tests, and documentation

Documentation

  • Links new API documentation in readme
  • Documentation in example plot_iris_from_sklearn.py explains 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

19 Jan 10:13

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1.4
  • Adds unscented transform to MVN
  • Extend documentation in readme