emst_mlpack | R Documentation |
Provides access to the implementation of the Dual-Tree Boruvka
algorithm from the mlpack
package (if available).
It is based on kd-trees and is fast for (very) low-dimensional
Euclidean spaces. For higher dimensional spaces (say, over 5 features)
or other metrics, use the parallelised Prim-like algorithm implemented
in mst()
.
emst_mlpack(X, leaf_size = 1, naive = FALSE, verbose = FALSE)
X |
a numeric matrix (or an object coercible to one, e.g., a data frame with numeric-like columns) |
leaf_size |
size of leaves in the kd-tree, controls the trade-off between speed and memory consumption |
naive |
logical; whether to use the naive, quadratic-time algorithm |
verbose |
logical; whether to print diagnostic messages |
An object of class mst
, see mst()
for details.
Marek Gagolewski and other contributors
March W.B., Ram P., Gray A.G., Fast Euclidean Minimum Spanning Tree: Algorithm, Analysis, and Applications, Proc. ACM SIGKDD'10, 2010, 603-611, https://mlpack.org/papers/emst.pdf.
Curtin R.R., Edel M., Lozhnikov M., Mentekidis Y., Ghaisas S., Zhang S., mlpack 3: A fast, flexible machine learning library, Journal of Open Source Software 3(26), 2018, 726.
The official online manual of genieclust at https://genieclust.gagolewski.com/
Gagolewski M., genieclust: Fast and robust hierarchical clustering, SoftwareX 15:100722, 2021, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.softx.2021.100722")}.
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