addClustering: Clustering addition

In RclusTool: Graphical Toolbox for Clustering and Classification of Data Frames

Description

adds a new clustering to an existing set of clusterings (replaces if exists).

Usage

addClustering(clustering, new.clustering.name, new.cluster.summary, new.label)

Arguments

clustering	list containing a set of clustering results.
new.clustering.name	string naming the clustering to add.
new.cluster.summary	summary object containing statistics about the new clustering.
new.label	vector of labels

Details

addClustering adds a new clustering to an existing set of clusterings (replaces if exists)

Value

updated list of clusterings.

Examples

dat <- rbind(matrix(rnorm(100, mean = 0, sd = 0.3), ncol = 2), 
             matrix(rnorm(100, mean = 2, sd = 0.3), ncol = 2), 
             matrix(rnorm(100, mean = 4, sd = 0.3), ncol = 2))

tf1 <- tempfile()
write.table(dat, tf1, sep=",", dec=".")

x <- importSample(file.features=tf1, dir.save=tempdir())

res_new <- KmeansQuick(x$features$initial$x, K=3)
labels_new <- formatLabelSample(res_new$cluster, x)
cluster.summary.new <- clusterSummary(x, labels_new)

x$clustering <- addClustering(clustering=x$clustering, new.clustering.name='clusterin_test', 
                              new.cluster.summary=cluster.summary.new, new.label=labels_new)
 

RclusTool documentation built on Feb. 4, 2020, 5:08 p.m.