integer. Number of repetitions of the hair-top point.
smile.coef
numeric. Coefficient for quadratic term used for
generation of mouth-points. Positive values=>smile.
dMoNo
number. Distance from mouth to nose.
dNoEy
number. Minimum vertical distance from mouth to eyes.
Value
An n times p numeric matrix with attributes
groupinga factor giving the cluster memberships of the points.
indexlista list of six vectors containing the indices of points
belonging to the six groups.
Details
The function generates a nice benchmark example for cluster
analysis.
There are six "clusters" in this data, of which the first five are
clearly homogeneous patterns, but with different distributional
shapes and different qualities of separation. The clusters are
distinguished only in the first two dimensions. The attribute
grouping is a factor giving the cluster numbers, see below.
The sixth group of
points corresponds to some hairs, and is rather a collection of
outliers than a cluster in itself. This group contains
nrep.top+2 points. Of the remaining points, 20% belong to
cluster 1, the chin (quadratic function plus noise).
10% belong to cluster 2, the right eye (Gaussian). 30% belong to
cluster 3, the mouth (Gaussian/squared Gaussian).
20% belong to cluster 4, the nose (Gaussian/gamma), and
20% belong to cluster 5, the left eye (uniform).
The distributions of the further
variables are homogeneous over
all points. The third dimension is exponentially distributed, the
fourth dimension is Cauchy distributed, all further distributions are
Gaussian.
Please consider the source code for exact generation of the clusters.
set.seed(4634)
face <- rFace(600,dMoNo=2,dNoEy=0)
grface <- as.integer(attr(face,"grouping"))
plot(face, col = grface)
# pairs(face, col = grface, main ="rFace(600,dMoNo=2,dNoEy=0)")