I am running a hot spot analysis for clusters of points within Myanmar using model builder. As the country is long and has many coastal and inland borders, I think the lack of data outside the country is affecting the result.
Some analysts consider Delaunay triangulation a way to construct natural neighbors for a set of features. This method is a good option when your data includes island polygons (isolated polygons that do not share any boundaries with other polygons) or in cases where there is a very uneven spatial distribution of features. It is not appropriate when you have coincident features, however. Similar to the K nearest neighbors method, Delaunay triangulation ensures every feature has at least one neighbor but uses the distribution of the data itself to determine how many neighbors each feature gets.
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