- If you make use of this DDVFA code please cite the following paper
[1] L. E. Brito da Silva, I. Elnabarawy, and D. C. Wunsch II, "Distributed dual vigilance fuzzy adaptive resonance theory learns online, retrieves arbitrarily-shaped clusters, and mitigates order dependence," Neural Networks. To appear.
and refer to this Applied Computational Intelligence Laboratory (ACIL) Github repository as
[2] L. E. Brito da Silva, I. Elnabarawy, and D. C. Wunsch II, "Distributed Dual Vigilance Fuzzy ART," 2019.
[Online].
Available: https://github.com/ACIL-Group/DDVFA
- The data sets used in the experiments section of the Distributed Dual Vigilance Fuzzy ART paper are available at:
-
UCI machine learning repository:
http://archive.ics.uci.edu/ml -
Fundamental Clustering Problems Suite (FCPS):
https://www.uni-marburg.de/fb12/arbeitsgruppen/datenbionik/data?language_sync=1 -
Datasets package:
https://www.researchgate.net/publication/239525861_Datasets_package -
Clustering basic benchmark:
http://cs.uef.fi/sipu/datasets
- The "main_example.m" file contains an example of usage of the code provided.