ROCDataAccessors {kebabs} | R Documentation |
ROCData Accessors
## S4 method for signature 'ROCData' auc(object)
object |
an object of class |
auc
: returns a numeric value
tpr
: returns a numeric vector
fpr
: returns a numeric vector
auc
:
returns the area under the ROC curve.
tpr
:
returns the true positive rate values as numeric vector.
fpr
:
returns the false positive rate values as numeric vector.
Johannes Palme <kebabs@bioinf.jku.at>
http://www.bioinf.jku.at/software/kebabs
J. Palme, S. Hochreiter, and U. Bodenhofer (2015) KeBABS: an R package
for kernel-based analysis of biological sequences.
Bioinformatics, 31(15):2574-2576, 2015.
DOI: 10.1093/bioinformatics/btv176.
## create kernel object for normalized spectrum kernel specK5 <- spectrumKernel(k=5) ## Not run: ## load data data(TFBS) ## select 70% of the samples for training and the rest for test train <- sample(1:length(enhancerFB), length(enhancerFB) * 0.7) test <- c(1:length(enhancerFB))[-train] ## perform training - feature weights are computed by default model <- kbsvm(enhancerFB[train], yFB[train], specK5, pkg="LiblineaR", svm="C-svc", cost=15) preddec <- predict(model, enhancerFB[test], predictionType="decision") rocdata <- computeROCandAUC(preddec, yFB[test], allLabels=unique(yFB)) ## accessor for auc auc(rocdata) ## End(Not run)