recluster: Re-clustering micro-clusters

In stream: Infrastructure for Data Stream Mining

Re-clustering micro-clusters

Description

Use an *offline macro clustering algorithm to recluster micro-clusters into a final clusters.

Usage

recluster(macro, micro, type = "auto", ...)

## S3 method for class 'DSC_Macro'
recluster(macro, micro, type = "auto", ...)

Arguments

macro	an empty DSC_Macro.
micro	an updated DSC_Micro with micro-clusters.
type	controls which clustering is used from micro. Typically auto.
...	additional arguments passed on.

Details

Takes centers and weights of the micro-clusters and applies the macro clustering algorithm.

See DSC_TwoStage for a convenient combination of micro and macro clustering.

Value

The object macro is altered in place and contains the clustering.

Author(s)

Michael Hahsler

See Also

Other DSC: DSC_Macro(), DSC_Micro(), DSC_R(), DSC_SlidingWindow(), DSC_Static(), DSC_TwoStage(), DSC(), animate_cluster(), evaluate.DSC, get_assignment(), plot.DSC(), predict(), prune_clusters(), read_saveDSC

Examples

set.seed(0)
### create a data stream and a micro-clustering
stream <- DSD_Gaussians(k = 3, d = 3)

### sample can be seen as a simple online clusterer where the sample points
### are the micro clusters.
sample <- DSC_Sample(k = 50)
update(sample, stream, 500)
sample

### recluster using k-means
kmeans <- DSC_Kmeans(k = 3)
recluster(kmeans, sample)

### plot clustering
plot(kmeans, stream, type = "both", main = "Macro-clusters (Sampling + k-means)")

stream documentation built on March 7, 2023, 6:09 p.m.