google maps - How to cluster latitude-longitude data based on fixed radius from centroid as the only constraint? -

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i have around 200k latitude & longitude data points. how can cluster them each clusters have latitude & longitude points strictly within radius = 1 km centroid only?

i tried leadercluster algorithm/package in r eventhough specify radius =1 km not strictly enforcing i.e. give clusters lot of point 5 - 10 kms cluster centroid within same cluster. not meeting requirement.

number of points in cluster can vary & not problem.

is there way enforce strict radius constraint in heirarchical or clustering algorithm? looking steps & implementation in r/python. tried searching in stackoverflow couldn't find solution in r/python.

how visualize cluster centroids in google maps after clustering in done?

edit

parameters using in elki. please verify enter image description here

this not clustering, set cover type of problem. @ least if looking good cover. clustering algorithm finding structure in data; looking forced quantization.

anyway, here 2 strategies can try e.g. in elki:

  • canopy preclustering t1=t2=your radius. should yield greedy approximation cover scenario.
  • complete linkage hierarchical agglomerative clustering, cut @ desired height. expensive (o(n^3)). 2 points in same cluster have @ distance, bit stricter requirement.

beware should using haversine ("geo") distances, not euclidean!


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