Implementation of the DBSCAN algorithm using largeVis datastructures.
lv_dbscan(edges, neighbors, eps = Inf, minPts = nrow(neighbors - 1),
verbose = getOption("verbose", TRUE))An `edgematrix` object. Alternatively, a largeVis object,
in which case edges and neighbors will be taken from the edges and knns parameters, respectively.
An adjacency matrix of the type produced by randomProjectionTreeSearch
See dbscan.
See dbscan.
Vebosity level.
A dbscan object.
The DBSCAN algorithm attempts to find clusters of a minimum density given by eps. This
implementation leverages the nearest neighbor data assembled by largeVis.
Martin Ester, Hans-Peter Kriegel, Jorg Sander, Xiaowei Xu (1996). Evangelos Simoudis, Jiawei Han, Usama M. Fayyad, eds. A density-based algorithm for discovering clusters in large spatial databases with noise. Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD-96). AAAI Press. pp. 226-231. ISBN 1-57735-004-9.