Labels every point in the array with a cluster number, or NA when the
point is noise. One label per row, in the order the points were given.
Details
DBSCAN grows a cluster from any point with at least min_points neighbours
within eps. Points reachable from that core join the cluster, and points
that never become reachable are noise. Unlike k-means it finds clusters of
any shape and does not need the count up front.
Clustering is over the whole array, not within each row, so eps and
min_points are single values rather than one per row. Cluster numbers
start at 1 and mean nothing beyond grouping. A row that is not a single
point, or is null, takes no part in the clustering and comes back null.
See also
Other cluster:
ga_kmeans(),
ga_outlier_scores()