This class represents the extensible Markov Model. It consists
of a simple data stream clustering algorithm (class "tNN") and
a temporal layer (class "TRACDS").
Objects can be created using the creator function EMM or by
directly calling new("EMM", ...). Most slots for the extended
classes can be used as parameters for EMM.
The slots are described in corresponding the extended classes (see section Extends).
signature(x = "EMM"): Make a copy of the EMM object.
Making explicit copies is necessary since the subclasses store
information in environments which are not copied for regular
assignements.
signature(x = "EMM"): Returns the size of
the EMM (number of clusters/states).
M.H. Dunham, Y. Meng, J. Huang (2004): Extensible Markov Model, In: ICDM '04: Proceedings of the Fourth IEEE International Conference on Data Mining, pp. 371--374.
build,
fade,
merge_clusters,
plot,
prune,
rare_clusters,
rare_transitions,
remove_clusters,
remove_transitions,
remove_selftransitions,
recluster, and
score.