buildClusteringSample: Clustering loading

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

Clustering loading

Description

Load a clustering result from a csv file into a data.sample object.

Usage

buildClusteringSample(filename.csv, data.sample, noise.cluster = "Noise")

Arguments

filename.csv	character vector specifying the path and the name of the csv file containing the clustering result.
data.sample	matrix of raw data (point by line).
noise.cluster	character name of the cluster "Noise".

Details

buildClusteringSample builds a clustering result from a csv file to be later embedded into a data.sample object

Value

The function returns a list 'clustering' containing:

label	vector of labels.
summary	data.frame containing clusters summaries (min, max, sum, average, sd).
K	number of clusters.

See Also

saveClustering

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)

lab <- data.frame(ID=1:nrow(dat), label=c(rep("Cluster 1",50), rep("Cluster 2",50), 
                                          rep("Cluster 3",50)))
tf2 <- tempfile()
write.table(lab, tf2, sep=",")

clustering <- buildClusteringSample(tf2, x)

RclusTool documentation built on Aug. 29, 2022, 9:07 a.m.