Recent Releases of kmodes
kmodes - 0.12.1
What's changed
- Fix for broken
fit_predictonKPrototypes(https://github.com/nicodv/kmodes/pull/176) - Improved validation of sample weights (https://github.com/nicodv/kmodes/pull/176)
Full Changelog: https://github.com/nicodv/kmodes/compare/0.12.0...0.12.1
- Python
Published by nicodv almost 4 years ago
kmodes - 0.12.0
What's changed
- Support for sample weights for both k-modes and k-prototypes algorithms, courtesy of @kklein (https://github.com/nicodv/kmodes/pull/174, https://github.com/nicodv/kmodes/pull/171)
- Add official support for Python 3.10 (https://github.com/nicodv/kmodes/pull/170)
- Bugfix for algorithm convergence (https://github.com/nicodv/kmodes/commit/370d64b1067331b413d641103a52bd4c636ac702)
- Switch internally to
pytestfromnose(https://github.com/nicodv/kmodes/pull/170) - Some small fixes and cleanups
Full Changelog: https://github.com/nicodv/kmodes/compare/0.11.1...0.12.0
- Python
Published by nicodv almost 4 years ago
kmodes - 0.11.1
What's Changed
- 155: Make labelscost function public by @nicodv in https://github.com/nicodv/kmodes/pull/156
- Iterations were running for 1 more than expected by @nicodv in https://github.com/nicodv/kmodes/pull/160
- Change feature array initialization dtype to uint32 by @rggelles in https://github.com/nicodv/kmodes/pull/166. This reduces memory footprint significantly.
- Drop support for missing values, following
scikit-learn: https://github.com/nicodv/kmodes/commit/a20f6ed6567f4c0d5c5c9ad70ca86a6b77ab522f
Full Changelog: https://github.com/nicodv/kmodes/compare/0.11.0...0.11.1
- Python
Published by nicodv over 4 years ago
kmodes - 0.10.2
- Added Jaccard dissimilarity function, courtesy of @BikashPandey17 (#129 )
- Return the costs per epoch after training, courtesy of @daffidwilde (#79 )
- Python 3.8 now supported
- Python 3.4 no longer supported because
sklearndropped it too - Various bugfixes and improvements
- Python
Published by nicodv almost 6 years ago
kmodes - 0.7
- Categorical variables are now automatically encoded and decoded between original data values and integers (used internally by k-modes). User does not have to use to the categorical variable mapping anymore when looking at the cluster centroids.
- Support for custom dissimilarity measures
- Python 3.6 support
- More robust manual initialization
- Python
Published by nicodv almost 6 years ago
kmodes - 0.8
- Huge speedup for k-prototypes, especially for large numbers of samples (#45). A k-prototypes benchmark script is included in examples now.
- Offer an implementation of Ng's dissimilarity measure, which could improve convergence (#37).
- Allow pandas DataFrames to be presented to the algorithm, instead of just numpy arrays (#40).
- Improved handling of dependencies (#49, #53).
- Various small bugfixes and improvements.
- Python
Published by nicodv almost 6 years ago
kmodes - 0.10.0
- Support for more than 256 clusters
- Optional parallel execution of the multiple initialization runs (courtesy of @rphes )
- Enhanced error checking when using pandas DataFrames as inputs to the algorithms
- Various bug fixes and improvements
- Semantic versioning from now on
- Python
Published by nicodv almost 6 years ago