I have a set of points(clusters) in higher dimension (30d to 100d). I need to identify concave hull of these points in an efficient manner. Is there a way to do get the exact concave hull or atleast approximate concave hull of these set of points? Further, if we have a set of points identified as a border point, is there a way to verify whether the points are actually border points?
In 100d, almost every point will be on the convex hull.
Just remember that a rectangle in 2d has 4 corners, but in 100d, it has 2^100 corners.
As an extremely rough approximation, take the minimum and maximum along each axis. If it is unique, the point is on the hull. For additional points, you can sample some random projections.
But again, the expected behaviour is that almost every point is on the hull, because it is the smallest or largest in some linear combination of features.