SandroMartens / ds2l-som

A Local Density-based Simultaneous Two-level Algorithm for Topographic Clustering

DS2L-SOM

DS2L-SOM is clustering algorithm based on Self Organizing Maps (SOM).

In a project

DSL2-SOM follows the scikit-learn API. We can train on data in the form (n_samples, n_features).

from ds2lsom import DS2LSOM
clusterer = DS2LSOM()
clusterer.fit(data)
labels = clusterer.predict(data)

Installing

git clone https://github.com/SandroMartens/ds2l-som.git
cd ds2l_som
pip install -e .

Dependencies

• Pandas
• Numpy
• NetworkX
• MiniSom
• scikit-learn

Notes

ToDo:

• Examples

References

• A Local Density-based Simultaneous Two-level Algorithm for Topographic Clustering, Guénaël Cabanes and Younès Bennani, 2008
• Enriched topological learning for cluster detection and visualization, Guénaël Cabanes, Younès Bennani and Dominique Fresneau, 2012