Update a clustering model by clustering a number of input points from a data stream into a clustering object.
Usage
# S3 method for DSC_R
update(object, dsd, n = 1, verbose = FALSE, block=10000L, ...)
# S3 method for DSC_TwoStage
update(object, dsd, n = 1, verbose = FALSE,
block=10000L, ...)
# S3 method for DSO_Sample
update(object, dsd, n = 1, verbose = FALSE, ...)
# S3 method for DSO_Window
update(object, dsd, n = 1, verbose = FALSE, ...)
Arguments
object
an object of a subclass of DST (data stream mining task).
dsd
a DSD object (data stream).
n
number of points to cluster.
verbose
report progress.
block
maximal number of data points passed on at once to the algorithm.
This only is used since R loops are very slow.
...
extra arguments for clusterer.
Value
The updated model is returned invisibly for reassignment
(however, this is not necessary).
To obtain the updated model for a DSC (data stream clustering
model), call get_centers() on the DSC object.
Details
update takes n times a single
data points out of the DSD updates the model in object.
Note that update directly
modifies the object (which is a reference class) and
thus the result does not need to be reassigned to the object name.
See Also
DSC,
DSD, and
animation for producing an animation of the clustering process.