What’s new in the package

A catalog of new features, improvements, and bug-fixes in each release.

v0.4 (Feb 2023)

v0.3 (July 2022)

v0.2.7 (June 2021)

v0.2.6 (March 2020)

  • Updated for better Scikit-Learn v0.22 support

v0.2.5 (January 2018)

  • Added BilinearFilter

  • Added a permutation test for generic scikit-learn estimator

  • Stats module refactoring, with distance based t-test and f-test

  • Removed two way permutation test

  • Added FlatChannelRemover

  • Support for python 3.5 in travis

  • Added Shrinkage transformer

  • Added Coherences transformer

  • Added Embedding class.

v0.2.4 (June 2016)

  • Improved documentation

  • Added TSclassifier for out-of the box tangent space classification.

  • Added Wasserstein distance and mean.

  • Added NearestNeighbor classifier.

  • Added Softmax probabilities for MDM.

  • Added CSP for covariance matrices.

  • Added Approximate Joint diagonalization algorithms (JADE, PHAM, UWEDGE).

  • Added ALE mean.

  • Added Multiclass CSP.

  • API: param name changes in CospCovariances to comply to Scikit-Learn.

  • API: attributes name changes in most modules to comply to the Scikit-Learn naming convention.

  • Added HankelCovariances estimation

  • Added SPoC spatial filtering

  • Added Harmonic mean

  • Added Kullback leibler mean

v0.2.3 (November 2015)

  • Added multiprocessing for MDM with joblib.

  • Added kullback-leibler divergence.

  • Added Riemannian Potato.

  • Added sample_weight for mean estimation and MDM.