Version v0.8.1

Version 0.8.1

Version 0.8.0

API changes:

• The first argument in Clustergram.fit() is now X instead of data.

Enhancements:

• API: follow scikit-learn API conventions (#59)
• ENH: ensure that x ticks are only integers (#58)
• ENH: format time in verbose mode

Full Changelog: v0.7.0...v0.8.0

Version 0.7.0

Enhancements:

• ENH: allow weighting by a custom principal component (#35)

Compatibility notes:

• clustergram now requires Python 3.8
• RAPIDS.AI implementation has been tested with version 22.12.

Minor notes:

• examples dictionary has been removed. Refer to the notebooks in the documentation.

Version v0.6.0

Enhancements:

• ENH: optionally measure BIC during GMM (#21)

Bug fixes:

• BUG: cuML non-weighted plot fix (#25)

Full Changelog: v0.5.1...v0.6.0

Version v0.5.1

Bugfix for from_data method with non-default indices.

Bugs:

• BUG: cluster centers empty due to index mismatch (#19)

Version v0.5.0

Clustergram now supports interactive plotting using a new .bokeh() method based on BokehJS. It
can be handy for the exploration of larger and more complex clustergrams or those with significant outliers.

Enhancements:

• ENH: support interactive bokeh plots (#14)
• ENH: skip k=1 in K-Means implementations (#18)

• documentation restructuring

Version v0.4.0

Spring comes with native hierarchical clustering and the ability to create clustergam from a manual input.

Enhancements:

• ENH: support hierarchical clustering using scipy (#11)
• ENH: from_data and from_centers methods (#12)

Version 0.3.0

API chages:

• pca_weighted is now keyword of Clustergram.plot() not init.

Enhancements:

• Support MiniBatchKMeans (sklearn)
• Custom __repr__
• Expose cluster labels obtained during the loop
• Expose cluster centers
• Silhouette score
• Calinski and Harabasz score
• Davies-Bouldin score

Version 0.2.1

Minor release updating documentation to acknowledge that clustergram can be installed from conda-forge.

Version 0.2.0

Version 0.2.0 brings support of Gaussian Mixture Models (using scikit-learn) and few minor changes.

Enhancements:

• Gaussian Mixture Model support (#4)
• Verbosity - Clustergram now indicates the progress
• Additional arguments can be passed to the PCA object

Bug fixes:

• BUG: avoid LinAlgError: singular matrix