roc {DirichletMultinomial} | R Documentation |
Returns a data.frame
summarizing the cummulative true- and
false-positive probabilities from expected and observed
classifications.
roc(exp, obs, ...)
exp |
|
obs |
Predicted probability of assignment to the group identified
by |
... |
Additional arguments, available to methods. |
A data.frame
with columns
TruePositive |
Cummulative probability of correct assignment. |
FalsePositive |
Cummulative probability of incorrect assignment. |
Martin Morgan mailto:mtmorgan@fhcrc.org
library(lattice) ## count matrix fl <- system.file(package="DirichletMultinomial", "extdata", "Twins.csv") count <- t(as.matrix(read.csv(fl, row.names=1))) ## phenotype fl <- system.file(package="DirichletMultinomial", "extdata", "TwinStudy.t") pheno0 <- scan(fl) lvls <- c("Lean", "Obese", "Overwt") pheno <- factor(lvls[pheno0 + 1], levels=lvls) names(pheno) <- rownames(count) ## count data used for cross-validation, and cross-validation count <- csubset(c("Lean", "Obese"), count, pheno) data(bestgrp) ## true, false positives from single-group classifier bst <- roc(pheno[rownames(count)] == "Obese", predict(bestgrp, count)[,"Obese"]) head(bst) ## lattice plot xyplot(TruePostive ~ FalsePositive, bst, type="l", xlab="False Positive", ylab="True Positive")