Self-Organised Direction Aware Data Partitioning Algorithm

Source code of SODA Algorithm for data partitioning/clustering.
182 téléchargements
Mise à jour 15 nov. 2018

Afficher la licence

The package contains:
1. The recently introduced Self-Organised Direction Aware Data Partitioning Algorithm (SODA);
2. A demo for offline data partitioning;
3. A demo for conducting hybrid between the offline prime and the evolving extension.

SODA algorithm is for data partitioning.

Data partitioning is very close to clustering, but the end result will be the data clouds with irregular shapes instead of clusters with certain shapes.

Reference:
X. Gu, P. Angelov, D. Kangin, J. Principe, Self-organised direction aware data partitioning algorithm, Information Sciences, vol.423, pp. 80-95 , 2018.

If this code is helpful, please cite the above paper.

For any queries about the codes, please contact Prof. Plamen P. Angelov (p.angelov@lancaster.ac.uk) and Dr. Xiaowei Gu (x.gu3@lancaster.ac.uk)

Programmed by Xiaowei Gu

Citation pour cette source

X. Gu, P. Angelov, D. Kangin, J. Principe, Self-organised direction aware data partitioning algorithm, Information Sciences, vol.423, pp. 80-95 , 2018.

Compatibilité avec les versions de MATLAB
Créé avec R2018a
Compatible avec toutes les versions
Plateformes compatibles
Windows macOS Linux
Catégories
En savoir plus sur Statistics and Machine Learning Toolbox dans Help Center et MATLAB Answers

Community Treasure Hunt

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

Start Hunting!
Version Publié le Notes de version
1.1.2.0

Updated Description.

1.1.1.0

Update the description

1.1.0.0

The output and input of the algorithm are reconstructed to an more convenient form for users.
The comments of the code are updated.
Update the description of the code

1.0.0.0