PySubCMedians

Authors: Sergio Peignier, Christophe Rigotti, Anthony Rossi and Guillaume Beslon

Python implementation of the SubCMedians algorithm. SubCMedians is a Subspace Clustering algorithm that extends the K-medians paradigm. SubCMedians is a simple hill climbing algorithm based on stochastic weighted local exploration steps. This median based algorithm exhibits satisfactory quality clusters when compared to well-established paradigms, while medians have still their own interests depending on the user application (robustness to noise/outliers and location optimality). Detailled description available in the paper "Weight-based search to find clusters around medians in subspaces" presented in the ACM SAC conference 2018.

Installation

Dependencies :

numpy
pandas
seaborn
scikit-learn
scipy
tqdm

Download files

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

Source Distribution

SubCMedians-0.0.3.tar.gz (9.2 kB view details)

Uploaded Apr 23, 2020 Source

Built Distribution

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

The dropdown lists show the available interpreters, ABIs, and platforms. Enable javascript to be able to filter the list of wheel files.

SubCMedians-0.0.3-py3-none-any.whl (31.6 kB view details)

Uploaded Apr 23, 2020 Python 3

File details

Details for the file SubCMedians-0.0.3.tar.gz.

File metadata

Download URL: SubCMedians-0.0.3.tar.gz
Upload date: Apr 23, 2020
Size: 9.2 kB
Tags: Source
Uploaded using Trusted Publishing? No
Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/46.1.3 requests-toolbelt/0.9.1 tqdm/4.44.1 CPython/3.7.4

File hashes

Hashes for SubCMedians-0.0.3.tar.gz
Algorithm	Hash digest
SHA256	`9585282cf5c81c82d4ecfeea0334049e00bb6abcce70810afb35c9fcb28e34b2`
MD5	`777be378afde46c8680855b6ade70f89`
BLAKE2b-256	`22b4e7e1cc5df93f29f85dcf609bc6aec651c155671956096f8603e07d744bfc`

See more details on using hashes here.

File details

Details for the file SubCMedians-0.0.3-py3-none-any.whl.

File metadata

Download URL: SubCMedians-0.0.3-py3-none-any.whl
Upload date: Apr 23, 2020
Size: 31.6 kB
Tags: Python 3
Uploaded using Trusted Publishing? No
Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/46.1.3 requests-toolbelt/0.9.1 tqdm/4.44.1 CPython/3.7.4

File hashes

Hashes for SubCMedians-0.0.3-py3-none-any.whl
Algorithm	Hash digest
SHA256	`b4e19c3fc9fbf2ba17727ddbe261422c262b5f18c630ae46b4664a6ee198db68`
MD5	`6434f8c2df529f62464ad1a57ab27561`
BLAKE2b-256	`71bd56cbec051dd8f2e845338f1107e6585b0cb6f7121558b6563ee04cfd4533`