The goal of the Hierarchical Cluster Analysis (HCA) method is to
find groupings in the input data matrix
. The input
metric is used to measure the similarity between the objects in
the input matrix
.
The distance matrix
is a matrix whose
elements say something about the similarities or
dissimilarities between objects. That is,
says something
about the similarity/dissimilarity between object
and object
.
We start with a warning: Since the
number of ways to permute the dataset is , and the number of
choices of metrics and methods is large, the different methods
often give different answers. The risk getting the result
``you want'', which could be wrong, is therefore high. Thus
the results should be analysed with great caution.