Re-clustering micro-clusters

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.

Value

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

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.

See also

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

Author

Michael Hahsler

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
#> Reservoir sampling 
#> Class: DSC_Sample, DSC_Micro, DSC_R, DSC 
#> Number of micro-clusters: 50 

### 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)")