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Class chac

Source: R/chac.R
chac.Rd

S3 class for Constrained Hierarchical Agglomerative Clustering results

Usage

# S3 method for class 'chac'
as.hclust(x, ...)

# S3 method for class 'chac'
print(x, ...)

# S3 method for class 'chac'
head(x, ...)

# S3 method for class 'chac'
summary(object, ...)

# S3 method for class 'chac'
plot(
  x,
  y,
  ...,
  mode = c("standard", "corrected", "total-disp", "within-disp", "average-disp"),
  nodeLabel = FALSE
)

diagnose(x, graph = TRUE, verbose = TRUE)

correct(x)

cutree_chac(tree, k = NULL, h = NULL)

Arguments

x, object, tree

an object of class 'chac'

...

for plot, arguments passed to the function plot.dendrogram. Default values for type and leaflab are respectively set to "triangle" and "none"

y

not used

mode

type of dendrogram to plot (see Details). Default to "standard"

nodeLabel

(logical) whether the order of merging has to be displayed or not. nodeLabel=TRUE prints orders of fusion at corresponding nodes. Default to FALSE

graph

(logical) whether the diagnostic plot has to be displayed or not. Default to TRUE

verbose

(logical) whether to print a summary of the result or not. Default to TRUE

k

an integer scalar or vector with the desired number of groups

h

numeric scalar or vector with heights where the tree should be cut. Only available when the heights are increasing

Value

The function plot.chac displays the dendrogram and additionally invisibly returns an object of class dendrogram with heights as specified by the user through the option mode.

diagnose invisibly exports a data frame with the numbers of decreasing merges described by the labels of the clusters being merged at this step and at the previous one, as well as the corresponding merge heights.

The function correct returns a chac objects with modified heights so as they are increasing. The new heights are calculated in an way identical to the option mode = "corrected" of the function plot.chac (see Details). In addition, the chac object has its field method modified from adjClust to adjClust-modified.

The function cutree_chac returns the clustering with k groups or with the groups obtained by cutting the tree at height h. If the heights are not increasing, the cutting of the tree is based on the corrected heights as provided by the function correct.

Details

Methods for class 'chac'

When plot.chac is called with mode = "standard", the standard dendrogram is plotted, even though, due to contingency constrains, some branches are reversed (decreasing merges). When plot.chac is called with mode = "corrected", a correction is applied to original heights so as to have only non decreasing merges). It does not change the result of the clustering, only the look of the dendrogram for easier interpretation.

Other modes are provided that correspond to different alternatives described in Grimm (1987):

  • in mode = "within-disp", heights correspond to within-cluster dispersion, i.e., for a corresponding cluster, its height is $$I(C) = \sum_{i \in C} d(i,g_C)$$ where \(d\) is the dissimilarity used to cluster objects and \(g_C\) is the center of gravity of cluster \(C\). In this case, heights are always non decreasing;

  • in mode = "total-disp", heights correspond to the total within-cluster dispersion. It is obtained from mode = "standard" by the cumulative sum of its heights. In this case, heights are always non decreasing;

  • in mode = "average-disp", heights correspond to the within-cluster dispersion divided by the cluster size. In this case, there is no guaranty that the heights are non decreasing. When reversals are detected, a warning is printed to advice the user to change the mode of the representation.

Grimm (1987) indicates that heights as provided by mode = "within-disp" are highly dependent on cluster sizes and that the most advisable representation is the one provided by mode = "total-disp". Further details are provided in the vignette "Notes on CHAC implementation in adjclust".

References

Grimm, E.C. (1987) CONISS: a fortran 77 program for stratigraphically constrained analysis by the method of incremental sum of squares. Computer & Geosciences, 13(1), 13-35.