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using Haversine distance in the DBSCAN algorithm #53
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Sure. There is an example with DBSCAN val gdbscan = new GDBSCAN(
DBSCAN.getNeighbours(epsilon = 1, distance = Kmeans.euclideanDistance),
DBSCAN.isCorePoint(minPoints = 2)
) The getNeighbours: (Point[T], Seq[Point[T]]) => Seq[Point[T]] = ??? You receive a single points.filter(neighbour => distance(neighbour.value, point.value) < epsilon) Hope that helps, |
Error:scalac: bad symbolic reference. A signature in Kmeans.class refers to term typesafe |
You can use the following snippet for the Haversine distance:
|
Is there a way to use Haversine distance instead of the euclidean distance in the DBSCAN algorithm?
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