Sparsified K-Means

Versione 1.0.0.0 (825 KB) da Stephen Becker
Extremely fast K-Means for big data
5.0
(1)
1,9K download
Aggiornato 18 apr 2018
Visualizza la licenza su GitHub

KMeans for big data using preconditioning and sparsification, Matlab implementation. This has three main features:
(1) it has good code: same accuracy and 100x faster than Matlab's K-means for some cases. It also incorporates the latest research, such as using K-Means++ for the initialization (Note: Matlab's R2015 K-Means now uses K-Means++ too). The code is well-documented and conforms to the conventions of Matlab's K-means function when possible.
(2) optionally, you can enable the precondition-and-sample feature which is a novel method to allow efficient processing when the datasets are extremely large and slow to work with.

(3) for datasets that are a few TB in size, you can use the read-from-disk option so that the entire matrix is never loaded into RAM all at once.

Installation is easy; run `setup_kmeans.m` and it will install the mex files for you if necessary, and setup the appropriate paths.

Cita come

Stephen Becker (2024). Sparsified K-Means (https://github.com/stephenbeckr/SparsifiedKMeans), GitHub. Recuperato .

Compatibilità della release di MATLAB
Creato con R2013a
Compatibile con qualsiasi release
Compatibilità della piattaforma
Windows macOS Linux
Categorie
Scopri di più su Statistics and Machine Learning Toolbox in Help Center e MATLAB Answers

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

private

Le versioni che utilizzano il ramo predefinito di GitHub non possono essere scaricate

Versione Pubblicato Note della release
1.0.0.0

Fixed typos in the description, no change to code (but github version is updated regularly)

Per visualizzare o segnalare problemi su questo componente aggiuntivo di GitHub, visita GitHub Repository.
Per visualizzare o segnalare problemi su questo componente aggiuntivo di GitHub, visita GitHub Repository.