| coef.hclust {cluster} | R Documentation |
Agglomerative / Divisive Coefficient for 'hclust' Objects
Description
Computes the “agglomerative coefficient” (aka “divisive
coefficient” for diana), measuring the
clustering structure of the dataset.
For each observation i, denote by m(i) its dissimilarity to the
first cluster it is merged with, divided by the dissimilarity of the
merger in the final step of the algorithm. The agglomerative
coefficient is the average of all 1 - m(i). It can also be seen
as the average width (or the percentage filled) of the banner plot.
coefHier() directly interfaces to the underlying C code, and
“proves” that only object$heights is needed to
compute the coefficient.
Because it grows with the number of observations, this measure should not be used to compare datasets of very different sizes.
Usage
coefHier(object)
coef.hclust(object, ...)
## S3 method for class 'hclust'
coef(object, ...)
## S3 method for class 'twins'
coef(object, ...)
Arguments
object |
an object of class Since For |
... |
currently unused potential further arguments |
Value
a number specifying the agglomerative (or divisive for
diana objects) coefficient as defined by Kaufman and Rousseeuw,
see agnes.object $ ac or diana.object $ dc.
Examples
data(agriculture)
aa <- agnes(agriculture)
coef(aa) # really just extracts aa$ac
coef(as.hclust(aa))# recomputes
coefHier(aa) # ditto