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2011OAC-data-norm-and-zscores.R (2.47 kB)
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nagae_models.py (7.86 kB)
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nagae_train.py (22.52 kB)
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GNN-CorrNet__Step1_SpatialGraphConstruction.ipynb (3.38 kB)
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GNN-CorrNet__Step2-GCN_SaptiallyEmbeddingGeneration.ipynb (20.1 kB)
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GNN-CorrNet__Step2-GS_SaptiallyEmbeddingGeneration.ipynb (79.94 kB)
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GNN-CorrNet__Step3_CorrNet-Kmeans.ipynb (9.14 kB)
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SFCM-geocmeans-oac.R (17.38 kB)
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SFCM-geocmeans-oac-PCA60.R (16.3 kB)
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kmeans-oac-PCA60.ipynb (36.5 kB)
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compare-geodemo-classifications.R (1.47 kB)
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compare-geodemo-classifications-report.Rmd (25.36 kB)
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compare-geodemo-evaluation-summary.R (7.15 kB)
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Code for "A graph neural network framework for spatial geodemographic classification"
This repository contains the code necessary to implement the geodemographic classifications defined through our graph convolutional neural network framework for spatial geodemographic classification (forthcoming), as well as three baseline models created using spatial fuzzy c-means and evaluate them in comparison with the London Output Area Classification by Singleton and Longley (2015).
References
Singleton A D, Longley P A (2015) The Internal Structure of Greater London: A Comparison of National and Regional Geodemographic Models. Geo: Geography and Environment. Available from: dx.doi.org/10.1002/geo2.7
