The Spatial C(K)luster Analysis by Tree Edge Removal (SKATER). The Spatial C(K)luster Analysis by Tree Edge Removal (SKATER) algorithm introduced by Assuncao et al. (2006) is based on the optimal pruning of a minimum spanning tree that reflects the contiguity structure among the observations. It provides an optimized algorithm to prune to tree into several clusters that their values of selected variables are as similar as possible.
The node is based on the package pygeoda and here are related tools and references:
The number of user-defined clusters.
The seed for the random number generator.
Select the geometry column to implement spatial clustering.
Select the bound column for clusters with minibound.
Select columns for calculating attribute distance.
The sum of the bounding variable in each cluster must be greater than this minimum value.
Input spatial weight mode.
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