https://github.com/ap6yc/adaptive_resonance
A PyPI python module for adaptive resonance theory (ART).
https://github.com/ap6yc/adaptive_resonance
Last synced: 6 months ago
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A PyPI python module for adaptive resonance theory (ART).
- Host: GitHub
- URL: https://github.com/ap6yc/adaptive_resonance
- Owner: AP6YC
- License: gpl-3.0
- Created: 2020-06-26T16:07:25.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2020-07-01T21:10:47.000Z (about 6 years ago)
- Last Synced: 2025-02-02T15:31:25.243Z (over 1 year ago)
- Size: 18.6 KB
- Stars: 0
- Watchers: 5
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# adaptive_resonance
A PyPI python module for adaptive resonance theory (ART).
| **Documentation** | **Build Status** | **Coverage** |
|:------------------:|:----------------:|:------------:|
This package is developed and maintained by [Sasha Petrenko](https://github.com/AP6YC) with sponsorship by the [Applied Computationa Intelligence Laboratory (ACIL)](https://acil.mst.edu/).
# Leveraged Repositories
- [ACIL Organization GitHub](https://github.com/ACIL-Group)
- MATLAB
- [DDVFA](https://github.com/ACIL-Group/DDVFA): Companion MATLAB implementation of distrubuted dual vigilance fuzzy ART.
- [DVFA](https://github.com/ACIL-Group/DVFA): Companion MATLAB code for Dual Vigilance Fuzzy ART
- [iCVI-toolbox](https://github.com/ACIL-Group/iCVI-toolbox): A MATLAB toolbox for incremental/batch cluster validity indices
- [CVIFA](https://github.com/ACIL-Group/CVIFA): Companion MATLAB implementation of validity index-based vigilance test fuzzy ART.
- [VAT-FA](https://github.com/ACIL-Group/VAT-FA): Companion MATLAB code for VAT + Fuzzy ART.
- [BARTMAP-CF](https://github.com/ACIL-Group/BARTMAP-CF): Companion MATLAB code for BARTMAP-based collaborative filtering
- Python
- [NuART-Py](https://github.com/ACIL-Group/NuART-Py): An internal ACIL python package for ART neural networks.
- [DVHA](https://github.com/ACIL-Group/DVHA): An python implementation of dual vigilance hypersphere ART.
# Datasets
1. UCI machine learning repository:
http://archive.ics.uci.edu/ml
2. Fundamental Clustering Problems Suite (FCPS):
https://www.uni-marburg.de/fb12/arbeitsgruppen/datenbionik/data?language_sync=1
3. Datasets package:
https://www.researchgate.net/publication/239525861_Datasets_package
4. Clustering basic benchmark:
http://cs.uef.fi/sipu/datasets