stream (version 1.1-1)

update: Update a Data Stream Clustering Model

Description

Update a clustering model by clustering a number of input points from a data stream into a clustering object.

Usage

## S3 method for class 'DSC_R':
update(object, dsd, n = 1, verbose = FALSE, block=10000L, ...)
## S3 method for class 'DSC_TwoStage':
update(object, dsd, n = 1, verbose = FALSE, 
  block=10000L, ...)
## S3 method for class 'DSO_Sample':
update(object, dsd, n = 1, verbose = FALSE, ...)
## S3 method for class '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.

Examples

stream <- DSD_Gaussians(k=3)
dstream <- DSC_DStream(gridsize=.05)  

update(dstream, stream, 500)
plot(dstream, stream)