Distance of categorical data (Jaccard,Rand and adjusted Rand index)
randIndFx
calculates distance of categorical data (as Rand Index, Adjusted Rand Index or Jaccard Index).
Note: uses/requires package flexclust
Methods so far available (via flexclust): "ARI" .. adjusted Rand Index, "RI" .. Rand index, "J" .. Jaccard, "FM" .. Fowlkes-Mallows.
randIndFx(ma, method = "ARI", adjSense = TRUE, silent = FALSE, callFrom = NULL)
ma |
(matrix) main input for distance calulation |
method |
(character) name of distance method (eg "ARI","RI","J","FM") |
adjSense |
(logical) allows introducing correlation/anticorrelation (interprete neg distance results as anti) |
silent |
(logical) suppres messages |
callFrom |
(character) allow easier tracking of message(s) produced |
distance matrix
comPart
in randIndex
set.seed(2016); tab2 <- matrix(sample(1:2,size=42,replace=TRUE),ncol=7) flexclust::comPart(tab2[1,],tab2[2,]) flexclust::comPart(tab2[1,],tab2[3,]) flexclust::comPart(tab2[1,],tab2[4,]) randIndFx(tab2,adjS=FALSE) cor(t(tab2)) randIndFx(tab2,adjS=TRUE)
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