graph - Best way to do clustering/segmentation on a multidimensional spatial data?

Question

I have a spatial grid with points having multidimensional data. What is the best way to do clustering or segmentation on this? To reiterate, each data point has a spatial coordinate and multi-dimensinal data associated (Multiple features), I want to make use of these features but also taking into account the spatial information.

I have tried building a graph with each spatial point connected to the nearest 5 spatial points with a directed weight as some mathematical metric (Jaccard similarity), then running community detection algorithms as Louvain/Leiden without success.

question from:https://stackoverflow.com/questions/65928295/best-way-to-do-clustering-segmentation-on-a-multidimensional-spatial-data

Answer 1

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