Max-P Greedy. A greedy algorithm to solve the max-p-region problem.
The so-called max-p regions model (outlined in Duque, Anselin, and Rey 2012) uses a different approach and considers the regionalization problem as an application of integer programming. In addition, the number of regions is determined endogenously.
The algorithm itself consists of a search process that starts with an initial feasible solution and iteratively improves upon it while maintaining contiguity among the elements of each cluster.
The node is based on the package pygeoda and here are related tools and references:
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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