View source: R/unsuperv_classification.R
WH_MAT_DIST | R Documentation |
The function extracts the L2 Wasserstein distance matrix from a MatH object.
WH_MAT_DIST(x, simplify = FALSE, qua = 10, standardize = FALSE)
x |
A MatH object (a matrix of distributionH). |
simplify |
A logic value (default is FALSE), if TRUE histograms are recomputed in order to speed-up the algorithm. |
qua |
An integer, if |
standardize |
A logic value (default is FALSE). If TRUE, histogram-valued data are standardized, variable by variable, using the Wasserstein based standard deviation. Use if one wants to have variables with std equal to one. |
A matrix of squared L2 distances.
Irpino A., Verde R. (2006). A new Wasserstein based distance for the hierarchical clustering of histogram symbolic data. In: Batanjeli et al. Data Science and Classification, IFCS 2006. p. 185-192, BERLIN:Springer, ISBN: 3-540-34415-2
DMAT <- WH_MAT_DIST(x = BLOOD, simplify = TRUE)
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