emst_mlpack: Euclidean Minimum Spanning Tree

Description

Provides access to an implementation of the Dual-Tree Borůvka algorithm based on kd-trees. It 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().

Usage

emst_mlpack(X, verbose = FALSE)

Arguments

X

a numeric matrix (or an object coercible to one, e.g., a data frame with numeric-like columns)

verbose

logical; whether to print diagnostic messages

Details

Calls emstreeR::mlpack_mst() and converts the result so that it is compatible with the output of mst().

If the emstreeR package is not available, an error is generated.

Value

An object of class mst, see mst() for details.

References

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), 726, 2018.