getClassification.Rd

% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/evaluate.R
\name{getClassification}
\alias{getClassification}
\title{getClassification}
\usage{
getClassification(modality, algorithmOutput, algorithmName = "mclust",
  validationData)
}
\arguments{
\item{modality}{numerical, for which modality the classification is calculated, 1 for unimodal,
2 for bimodal,...}

\item{algorithmOutput}{The formatted output of the algorithm}

\item{algorithmName}{The name of the evaluated algorithm}

\item{validationData}{The validationData behind the simulated gene
expression data frame}
}
\value{
a classification data frame that contains the number of
FN, FP, TN and TP
}
\description{
Returns the numbers of TN (TRUE Negative),TP (TRUE Positive),
FN (FALSE Negative) and FP (FALSE Positive) for one of the algorithm's
formatted outputs.
}
\details{
TN (TRUE Negative): validationData: unimodal, assigned scenario: unimodal

TP (TRUE Positive): validationData: bimodal, assigned scenario: bimodal

FN (FALSE Negative): validationData: bimodal, assigned scenario: unimodal
or
FN (FALSE Negative): validationData: unimodal/bimodal,
 assigned scenario: more than bimodal

FP (FALSE Positive): validationData: unimodal, assigned scenario: bimodal
}
\examples{
\dontrun{
params <- newParams(nGenes = list("1"=10,"2"=list("gauss"= 10,"gamma"= 10)))
simulation <- simulateExpression(params= params,verbose=FALSE)
expression <- simulation$expressionData
validationData <- simulation$validationData
mclustOutput <- useMclust(expression, verbose=FALSE)
getClassifications(modality = 2,validationData = validationData,
outputs = list("mclust" = mclustOutput))
}
}