Holds information about different clusters (classes, groups, labels) associated with a
sampleset object. Each
cluster is identified by a unique positive integer, called the
group identification
number (GID). For example, suppose that we have a
sampleset of
six human subjects, where numbers 1 and 4 are seniors, number 2 is infant, and numbers 3, 5
and 6 are adults. Then, their
assignment vector may look like
[9 1 5 9 5 5]
where 1 is the GID of the group 'infant', 5 is the GID of the group 'adult', and 9 is
the GID of the group 'senior'. Another important number that we associate with an assignment
vector is the
group consecutive number (GCN), which is just an integer that
determines the location of each group in a list of groups sorted by their GID. In our example,
the GCN vector would be [1 2 3] for the three groups 'infant', 'adult' and 'senior', in that
order, corresponding to their sorted GIDs [1 5 9].
If the GCN vector is identical to the GID vector, the grouping is called
consistent.
Otherwise, it is
inconsistent. The transformation between the two vectors is achieved
by the two vectors GID2GCN and GCN2GID. GID2GCN is a vector of length
max(GID), where
GID2GCN(ii)
is the GCN of GID
ii. NaN in entry
ii means that GID
ii is
nonexistent. In the above example the vector GID2GCN is
[1 NaN NaN NaN 2 NaN NaN NaN 3].
GCN2GID is the inverse transformation, a vector of length
max(GCN),
where
GCN2GID(ii) is the GID of the
ii'th group. In the above example the vector GCN2GID is [1 5 9].
Actually, the two vectors are related by
GCN2GID = find(~isnan(GID2GCN)).
A grouping may have several hierarchies. A
hierarchy is a division (finer division)
of a grouping. In our example, a finer hierarchy may be
[10 1 5 10 7 5]
where 1 is the GID of 'infant', 5 is the GID of 'male adult', 7 is the GID of 'female adult', and 10 is the
GID of 'senior'. Hierarchy A is called
coarser than hierarchy B (and hierarchy B is called
finer than hierarchy A) if B is a subdivision of A (B includes more groups than A). All
hierarchies are assumed to be
compatible with the first, coarsest, one (but not with each other),
and it is the sole responsibility of the user to verify that. An
incompatible hierarchy in
our example might be [6 1 5 9 5 6], as 6 is assigned to two samples that have different coarser grouping.
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