Skip to main content

Official Implementation of POCS-based Clustering Algorithm

Project description

POCS-based Clustering Algorithm

Paper Paper Blog Blog

Official implementation of the Projection Onto Convex Set (POCS)-based clustering algorithm.

Introduction

  • Algorithm:

Usage

Package

We release a package of this project on PyPI:

pip install pocs-based-clustering

Demo via Installed Package

test_pocs_clustering_package.ipynb

Demo via Local Script

python test_pocs_clustering_local.py

Results

Results on Clustering basic benchmark

Citation

Please cite our works if you utilize any data from this work for your study.

@inproceedings{tran2022pocs,
  title={POCS-based Clustering Algorithm},
  author={Tran, Le-Anh and Deberneh, Henock M and Do, Truong-Dong and Nguyen, Thanh-Dat and Le, My-Ha and Park, Dong-Chul},
  booktitle={2022 International Workshop on Intelligent Systems (IWIS)},
  pages={1--6},
  year={2022},
  organization={IEEE}
}

@article{tran2024cluster,
  title={Cluster Analysis via Projection onto Convex Sets},
  author={Tran, Le-Anh and Kwon, Daehyun and Deberneh, Henock Mamo and Park, Dong-Chul},
  journal={Intelligent Data Analysis},
  year={2024},
  publisher={IOS Press}
}

Have fun!

LA Tran

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pocs_based_clustering-1.3.0.tar.gz (9.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pocs_based_clustering-1.3.0-py3-none-any.whl (9.8 kB view details)

Uploaded Python 3

File details

Details for the file pocs_based_clustering-1.3.0.tar.gz.

File metadata

  • Download URL: pocs_based_clustering-1.3.0.tar.gz
  • Upload date:
  • Size: 9.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.7.9

File hashes

Hashes for pocs_based_clustering-1.3.0.tar.gz
Algorithm Hash digest
SHA256 c5b9d4c5195277b15c2ca20c56a5ca0e7d5aa6e4b39547b241fe325a1c79b385
MD5 c102c74b1fa59ecb389821e9aace2909
BLAKE2b-256 af949c9a5f1c82a55ad2a9045469ddd7afe1adba5073fc13f8ea0bb7a7a088ca

See more details on using hashes here.

File details

Details for the file pocs_based_clustering-1.3.0-py3-none-any.whl.

File metadata

File hashes

Hashes for pocs_based_clustering-1.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 365cc68612d3c29dcc1d32c4d71d7133ce5521299dc74eba39f8ab696e5e754f
MD5 ffe52c28df97ee48fc3ba7efd0a92c59
BLAKE2b-256 86824fe1dc1bdb854ccb2bc865eedff1fb89e044ed3b8dc34ccf199dc59b4938

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page