Spatially-Encouraged Spectral Clustering, a method of discovering clusters/deriving labels for spatially-referenced data with attribute/labels attached.
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spenc
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US_County_Level_Presidential_Results_08-16.csv
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README.md

Spatially-Encouraged Spectral Clustering

Build Status DOI

This repository provides the code & walks through how to use spatially-encouraged spectral clustering. Refer to the example notebook for more information on usage.

Usage reqiures scikit-learn and scipy. The package is released on pypi as spenc, so installation is available using:

pip install spenc

Citation

If you would like to reference this software, please cite its zenodo listing:

Wolf, Levi John. 2018. “Ljwolf/spenc: GISRUK”. Zenodo. doi:10.5281/zenodo.1219904.

And, for the paper defining the algorithm:

Wolf, Levi John. (In Review) "Spatially-Encouraged Spectral Clustering." International Journal of Geographic Information Science.

with a full preprint available at the Open Science Framework.