Metadata-Version: 2.1
Name: global-kmeans-pp
Version: 0.1.0
Summary: A library for implementing the global k-means and the global k-means++ clustering algorithms.
Author-email: Georgios Vardakas <g.vardakas@uoi.gr>
Maintainer-email: Georgios Vardakas <g.vardakas@uoi.gr>
License: MIT License
        
        Copyright (c) 2022 Giorgos Vardakas 
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
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Project-URL: Homepage, https://github.com/gvardakas/global-kmeans-pp
Project-URL: Issues, https://github.com/gvardakas/global-kmeans-pp/issues
Keywords: clustering,k-means,clustering error,global optimization,global k-means,k-means++,global k-means++
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE

# The Global $k$-mean++ clustering algorithm

The global $k$-means++ is an effective relaxation of the global $k$-means clustering algorithm, providing an ideal compromise between clustering error and execution speed. It is an effective way of acquiring quality clustering solutions akin to those of global $k$-means with a reduced computational load. It is an incremental clustering approach that dynamically adds one cluster center at each $k$ cluster sub-problem. For each $k$ cluster sub-problem, the method selects $L$ data points as candidates for the initial position of the new center using the effective $k$-means++ selection probability distribution. The selection method is fast and requires no extra computational effort for distance computations.

```
@article{vardakas2022global,
  title={Global $k$-means$++$: an effective relaxation of the global $k$-means clustering algorithm},
  author={Vardakas, Georgios and Likas, Aristidis},
  journal={arXiv preprint arXiv:2211.12271},
  year={2022}
}

@article{likas2003global,
  title={The global k-means clustering algorithm},
  author={Likas, Aristidis and Vlassis, Nikos and Verbeek, Jakob J},
  journal={Pattern recognition},
  volume={36},
  number={2},
  pages={451--461},
  year={2003},
  publisher={Elsevier}
}
```
