2021-12-16 13:01:44 +01:00
|
|
|
% Generated by roxygen2: do not edit by hand
|
2022-01-26 09:58:33 +01:00
|
|
|
% Please edit documentation in R/method_clustering.R
|
2021-12-16 13:01:44 +01:00
|
|
|
\name{clusteriness}
|
|
|
|
|
\alias{clusteriness}
|
|
|
|
|
\title{Perform a cluster analysis.}
|
|
|
|
|
\usage{
|
2022-06-16 19:45:59 +02:00
|
|
|
clusteriness(data, span = 1e+05, weight = 0.7, n_clusters = NULL)
|
2021-12-16 13:01:44 +01:00
|
|
|
}
|
|
|
|
|
\arguments{
|
|
|
|
|
\item{data}{The values that should be scored.}
|
|
|
|
|
|
|
|
|
|
\item{span}{The maximum span of values considered to be in one cluster.}
|
|
|
|
|
|
|
|
|
|
\item{weight}{The weight that will be given to the next largest cluster in
|
|
|
|
|
relation to the previous one. For example, if \code{weight} is 0.7 (the
|
|
|
|
|
default), the first cluster will weigh 1.0, the second 0.7, the third 0.49
|
|
|
|
|
etc.}
|
2022-06-16 19:45:59 +02:00
|
|
|
|
|
|
|
|
\item{n_clusters}{Maximum number of clusters that should be taken into
|
|
|
|
|
account. By default, all clusters will be regarded.}
|
|
|
|
|
}
|
|
|
|
|
\value{
|
|
|
|
|
A score between 0.0 and 1.0 summarizing how much the data clusters.
|
2021-12-16 13:01:44 +01:00
|
|
|
}
|
|
|
|
|
\description{
|
|
|
|
|
This function will cluster the data using \code{\link[stats:hclust]{stats::hclust()}} and
|
|
|
|
|
\code{\link[stats:cutree]{stats::cutree()}}. Every cluster with at least two members qualifies for
|
|
|
|
|
further analysis. Clusters are then ranked based on their size in relation
|
|
|
|
|
to the total number of values. The return value is a final score between
|
|
|
|
|
0.0 and 1.0. Lower ranking clusters contribute less to this score.
|
|
|
|
|
}
|
