clusterDensity {RclusTool} | R Documentation |
Clusters density computation
Description
Save density summaries results.
Usage
clusterDensity(
data.sample,
label,
space,
features.to.keep = colnames(data.sample$features[[space]]$x)
)
Arguments
data.sample |
list containing features, profiles and clustering results. |
label |
vector of labels. |
space |
space in which is the feature to deal with. |
features.to.keep |
vector of features names on which the summaries are computed. |
Details
clusterDensity computes the clusters density from a clustering result.
Value
out data.frame containing the density summaries.
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)
x <- computeUnSupervised(x, K=3, method.name="K-means")
label<-x[["clustering"]][["K-means_preprocessed"]][["label"]]
cluster.density <- clusterDensity(x, label, "preprocessed", features.to.keep='V1')
[Package RclusTool version 0.91.6 Index]