R_NX {coRanking} | R Documentation |
The
criterion
Description
A curve indicating the improvement of the embedding over a random embedding
for the neighborhood size . Values range from 0, for a random
embedding, to 1 for a perfect embedding.
Usage
R_NX(Q)
Arguments
Q |
a co-ranking matrix |
Details
is calculated as follows:
Counts the upper left -by-
block of
, i.e. it considers the preserved
ranks on the diagonal and the permutations within a neighborhood.
A resulting vale of 0
corresponds to a random embedding, a value of 1 to a perfect embedding of the
-ary neighborhood.
Value
A vector with the values for R_NX(K)
Author(s)
Guido Kraemer
References
Lee, J.A., Lee, J.A., Verleysen, M., 2009. Quality assessment of dimensionality reduction: Rank-based criteria. Neurocomputing 72.
Lee, J. A., Peluffo-Ordóñez, D. H., & Verleysen, M., 2015. Multi-scale similarities in stochastic neighbour embedding: Reducing dimensionality while preserving both local and global structure. Neurocomputing, 169, 246–261. https://doi.org/10.1016/j.neucom.2014.12.095