Self-Organised Direction Aware Data Partitioning Algorithm

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