This is a two-in-one package which provides interfaces to
both R and Python. It implements fast hierarchical clustering
routines on a set of dissimilarities. The R interface is
designed as a drop-in replacement for the function “hclust” in
the “stats” package and for the “flashClust“ package. It
provides the same functionality, with the benefit of a much
faster implementation. The Python interface is written as a
replacement for the “linkage” function in the
“scipy.cluster.hierarchy” module. Again, it provides the same
functionality as the original function but a much faster
implementation. For information on how to install the Python
files, see the file INSTALL in the source distribution.

c(person("Daniel", "Müllner", email =
"fastcluster@math.stanford.edu"), role = c("aut", "cph",
"cre"))
This is a two-in-one package which provides interfaces to
both R and Python. It implements fast hierarchical,
agglomerative clustering routines. Part of the functionality is
designed as drop-in replacement for existing routines:
“linkage” in the SciPy package “scipy.cluster.hierarchy”,
“hclust” in R's “stats” package, and the “flashClust” package.
It provides the same functionality, with the benefit of a much
faster implementation. Moreover, there are memory-saving
routines for clustering of vector data, which go beyond what
the existing packages provide. For information on how to
install the Python files, see the file INSTALL in the source
distribution.

person("Daniel", "Müllner", email =
"fastcluster@math.stanford.edu", role = c("aut", "cph", "cre"))

person("Daniel", "Müllner", email =
"muellner@math.stanford.edu", role = c("aut", "cph", "cre"))
This is a two-in-one package which provides interfaces to
both R and Python. It implements fast hierarchical,
agglomerative clustering routines. Part of the functionality is
designed as drop-in replacement for existing routines:
“linkage” in the SciPy package “scipy.cluster.hierarchy”,
“hclust” in R's “stats” package, and the “flashClust” package.
It provides the same functionality with the benefit of a much
faster implementation. Moreover, there are memory-saving
routines for clustering of vector data, which go beyond what
the existing packages provide. For information on how to
install the Python files, see the file INSTALL in the source
distribution.