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Dear authors,
is it possible to calculate inverse distances of every point to all other points and use the numbers as weights for Spatially Constrained Clustering instead of local neighborhood matrices (e. g. queen 0/1)?
Thank you.
The text was updated successfully, but these errors were encountered:
Dear authors,
is it possible to calculate inverse distances of every point to all other points and use the numbers as weights for Spatially Constrained Clustering instead of local neighborhood matrices (e. g. queen 0/1)?
Thank you.
The text was updated successfully, but these errors were encountered: