Clustering algorithms powered by Numpy
This is an fast implementation of K-Means, K-Means++ and C-Means with Numpy.
How to install ?
This package is distributed on https://pypi.org/project/clustering-algorithms and can be installed by the following command:
pip install clustering-algorithms
How to contribute ?
Comments and PR are very welcome. You can check the coding conventions by running the following command:
./scripts/bash/style.sh
Miscellaneous
Performance comparison of K-Means and C-Means
PYTHONPATH=. python ./scripts/python/performance.py
Plotting K-Means and C-Means
PYTHONPATH=. python ./scripts/python/plot.py
1 maintainer
Metadata
1 maintainer
Release files for clustering-algorithms 0.5.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| clustering_algorithms-0.5.0.tar.gz | 5.0 kB | Without provenance | Details for clustering_algorithms-0.5.0.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| clustering_algorithms-0.5.0-py3-none-any.whl | Python 3 | none | any | Details for clustering_algorithms-0.5.0-py3-none-any.whl |
Total release size: 11.7 kB
Release files / clustering_algorithms-0.5.0.tar.gz
| Download URL | clustering_algorithms-0.5.0.tar.gz |
|---|---|
| Size | 5.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
6fc88e0840229d14eafe16952b2379c8408694b85aff17c458a30af2d09e463f
|
|
BLAKE2b-256 checksum How to use checksums |
5d860286f5152c7a4d1b156ce9413e431b0f805c913036e8c12d46aaf0d7e2c4
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.9.6
|
Release files / clustering_algorithms-0.5.0-py3-none-any.whl
| Download URL | clustering_algorithms-0.5.0-py3-none-any.whl |
|---|---|
| Size | 6.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
49f5babc8bacc8a021b51664cd2c6d8d2114dc704fbe4825a86920fba495b6f1
|
|
BLAKE2b-256 checksum How to use checksums |
e084753095979f1b3d7267a4a69288e5279a4edb72cc9ad9ea5d551a932581c0
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.9.6
|
Security for clustering-algorithms 0.5.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
