#  K- Nearest Neighbor (K-NN) 

 



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K-NN is an open-source system designed to calculate K-nearest neighbors on geospatial big data. It is particularly useful for studies requiring nearest neighbor analysis, such as examining partisan segregation at the individual level for a dataset of 180 million U.S. voters. The open-source software is available on K-NN’s [GitHub](https://github.com/cga-harvard/KNN_analysis) for community access and use.

**Use-cases/Publications:**

- Brown J., Enos R. “[Measurement of Partisan Segregation for 180 Million US voters](https://www.nature.com/articles/s41562-021-01066-z.epdf)”, Nature Human Behaviour
- Kakkar D., Lewis B., Guan W. “[Interactive analysis of big geospatial data with high-performance computing: A case study of partisan segregation in the United States](https://onlinelibrary.wiley.com/doi/10.1111/tgis.12955)”, Transactions in GIS.



 



 

 See also:- [ Basic ](/page-type/basic)