r-cran-genieclust - 1.1.6-1 main

A retake on the Genie algorithm - a robust hierarchical clustering
method (Gagolewski, Bartoszuk, Cena, 2016
). Now faster and more memory efficient;
determining the whole hierarchy for datasets of 10M points in low
dimensional Euclidean spaces or 100K points in high-dimensional ones
takes only 1-2 minutes. Allows clustering with respect to mutual
reachability distances so that it can act as a noise point detector or a
robustified version of 'HDBSCAN*' (that is able to detect a predefined
number of clusters and hence it does not dependent on the somewhat
fragile 'eps' parameter).
.
The package also features an implementation of economic inequity indices
(the Gini, Bonferroni index) and external cluster validity measures
(partition similarity scores; e.g., the adjusted Rand, Fowlkes-Mallows,
adjusted mutual information, pair sets index).
.
See also the 'Python' version of 'genieclust' available on 'PyPI', which
supports sparse data, more metrics, and even larger datasets.