Recent Releases of kmodes

kmodes - 0.12.2

What's changed

  • Improve estimation of gamma for k-prototypes (https://github.com/nicodv/kmodes/pull/186)

Full Changelog: https://github.com/nicodv/kmodes/compare/0.12.1...0.12.2

- Python
Published by nicodv over 3 years ago

kmodes - 0.12.1

What's changed

  • Fix for broken fit_predict on KPrototypes (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 pytest from nose (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 - 0.11.0

  • Python 3.9 support
  • Minimum sklearn version upgrade to 0.22
  • Default init method for k-prototypes is now the Cao method (same as k-modes and in line with documentation), courtesy of @larroy
  • Optimizations

- Python
Published by nicodv about 5 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 sklearn dropped it too
  • Various bugfixes and improvements

- Python
Published by nicodv almost 6 years ago

kmodes - 0.9

  • Bugfixes

- 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

kmodes - 0.10.1

  • Improved pandas compatibility, courtesy of @Genie-Liu
  • Forward compatible with future scikit-learn versions that will no longer include joblib, courtesy of @trevorstephens

- Python
Published by nicodv almost 6 years ago