Description Usage Arguments Details Value Note References
Experimental implementation of the OPTICS algorithm.
1 2 |
edges |
A weighted graph of the type produced by |
neighbors |
An adjacency matrix of the type produced by |
eps |
See |
minPts |
See |
eps_cl |
See |
xi |
See |
useQueue |
Whether to process points in order of core distance. (See note.) |
verbose |
Vebosity level. |
This is an implementation of the OPTICS algorithm that attempts
to leverage the largeVis
nearest-neighbor search.
This implementation does not use the OPTICS neighbor-search strategy, in favor of using the pre-calculated
neighbor matrix produced incidentally by largeVis
. It is therefore a variant of OPTICS rather than an
implementation of the original, and the results vary slightly from those obtained by the implementations in
ELKI
and the dbscan
package.
An optics
object.
The useQueue
parameter controls the order in which points that have not yet been visisted are processed. If FALSE
,
points are processed in order of rows. If TRUE
, they are processed in ascending order of core distance. FALSE
is more
compatible with the implementations in the dbscan
package and in the ELKI
Java clustering package. TRUE
may produce
preferrable results.
Mihael Ankerst, Markus M. Breunig, Hans-Peter Kriegel, Jorg Sander (1999). OPTICS: Ordering Points To Identify the Clustering Structure. ACM SIGMOD international conference on Management of data. ACM Press. pp. 49-60.
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