dist.birch {birch} | R Documentation |
This function computes and returns the distance matrix computed by
passing the centers of the subclusters in the birch object to
dist
.
dist.birch(birchObject, ...)
birchObject |
An object created by the function
birch . |
... |
Further arguments passed to dist . |
This function is a wrapper for the dist
function, for
application on the centers of birch objects. It is provided as a
convenient mechanism for provided estimates of initial centers for the
kmeans.birch
function. An example of this is provided in the
section below.
An object of the class “dist”. See dist
for more details.
Justin Harrington harringt@stat.ubc.ca and Matias Salibian-Barrera matias@stat.ubc.ca
Harrington, J and Salibian-Barrera, M (2007) “Finding Approximate Solutions to Combinatorial Problems with Very Large Datasets using BIRCH”, submitted to Statistical Algorithms and Software, 2nd Special Issue Computational Statistics and Data Analysis. A draft can be found at http://www.stat.ubc.ca/~harringt/birch/birch.pdf.
Harrington, J and Salibian-Barrera, M (2008) “birch: Working with very large data sets”, submitted to Journal of Statistical Software. A draft can be found at http://www.stat.ubc.ca/~harringt/birch/birch-jss.pdf.
## Load a demo birch Object data(birchObj) ## Calculate the distances, perform hclust, and then ## find out which clustering corresponds to 2 groups bDist <- dist.birch(birchObj) hc <- hclust(bDist) clusters <- cutree(hc, 2) ## Calculate centers based on these clusters, and cluster with them centers <- rbind(summary(birchObj[clusters == 1,])$mean, summary(birchObj[clusters == 2,])$mean) kOut <- kmeans.birch(birchObj, centers)