RclusTool (version 0.91.61)

extractProtos: Prototypes extraction

Description

Extract prototypes of each cluster automatically, according to a clustering result, and save them in different directories. In order to catch the whole variability, each cluster is divided into several sub-clusters, and medoids of each sub-cluster are considered as prototypes.

Usage

extractProtos(
  data.sample,
  method,
  K.max = 20,
  kmeans.variance.min = 0.95,
  user.name = ""
)

Value

csv file containing the prototypes

Arguments

data.sample

list containing features, profiles and clustering results.

method

character vector specifying the clustering method (already performed) to use.

K.max

maximal number of clusters (K.max=20 by default).

kmeans.variance.min

elbow method cumulative explained variance > criteria to stop K-search.

user.name

character vector specifying the user name.

Details

extractProtos extracts prototypes automatically according to a clustering result, and save them in different directories

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=".")

dir.results <- tempdir()
x <- importSample(file.features=tf1, dir.save=dir.results)
x <- computeUnSupervised(x, K=3, method.name="K-means")

extractProtos(x, method = "K-means_preprocessed")