coef.hclust
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
Copyright (©) 1999–2012 R Foundation for Statistical Computing.
Licensed under the GNU General Public License.