Revision 20aefc9955133b9d3a2f3ea6366edd542e26701d authored by David Hofmeyr on 16 February 2018, 12:43:08 UTC, committed by cran-robot on 16 February 2018, 12:43:08 UTC
1 parent af98636
success_ratio.Rd
\name{success_ratio}
\alias{success_ratio}
\title{Evaluate External Valifity os a Binary Partition}
\description{
Computes the success ratio of a binary partition by comparing the solution with true class labels.
}
\usage{
success_ratio(assigned, labels)
}
\arguments{
\item{assigned}{a vector of cluster assignments made by a clustering algorithm.}
\item{labels}{a vector of true class labels to be compared with assigned.}
}
\value{
the success ratio of the cluster assignment solution.
}
\references{
Hofmeyr, D. (2016) Clustering by Minimum Cut Hyperplanes. \emph{IEEE Transactions on Pattern Analysis and Machine Intelligence}.
}
\examples{
## load optidigits dataset
data(optidigits)
## generate a binary partition using minimum normalised cut hyperplane
sol <- ncuth(optidigits$x)
## evaluate using success ratio
success_ratio(sol[[1]]$cluster, optidigits$c)
}
\keyword{file}

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