% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/manuscript-viz.R
\name{clustering_concordance}
\alias{clustering_concordance}
\title{Compare clustering solutions to each other (no ground truth needed)}
\usage{
clustering_concordance(labels_list)
}
\arguments{
\item{labels_list}{A named list of label vectors, all of the same length.}
}
\value{
A list with \code{agreement} (pairwise ARI matrix), \code{stability}
(mean pairwise co-membership per object) and \code{changed} (objects whose
label is not constant across solutions).
}
\description{
Given several labellings of the same objects (e.g. different weightings or
methods), compute their pairwise agreement (ARI) and each object's stability
-- how consistently it is co-clustered across the solutions. Useful for real
data where no ground truth is available.
}
\examples{
data(mosaic_toy)
v <- mosaic_labels(M_ABCpp(mosaic_toy$List, numsim = 40, NC = 3,
                           weighting = c("var", "var")), 3)
n <- mosaic_labels(M_ABCpp(mosaic_toy$List, numsim = 40, NC = 3,
                           weighting = c("nugget", "nugget")), 3)
clustering_concordance(list(var = v, nugget = n))$agreement
}
\seealso{
\code{\link{cluster_agreement}}, \code{\link{compare_clusterings}}
}
