precrec (version 0.14.4)

auc: Retrieve a data frame of AUC scores

Description

The auc function takes an S3 object generated by evalmod and retrieves a data frame with the Area Under the Curve (AUC) scores of ROC and Precision-Recall curves.

Usage

auc(curves)
# S3 method for aucs
auc(curves)

Value

The auc function returns a data frame with AUC scores.

Arguments

curves

An S3 object generated by evalmod. The auc function accepts the following S3 objects.

S3 object	# of models	# of test datasets
sscurves	single	single
mscurves	multiple	single
smcurves	single	multiple
mmcurves	multiple	multiple

See the Value section of evalmod for more details.

See Also

evalmod for generating S3 objects with performance evaluation measures. pauc for retrieving a dataset of pAUCs.

Examples

##################################################
### Single model & single test dataset
###

## Load a dataset with 10 positives and 10 negatives
data(P10N10)

## Generate an sscurve object that contains ROC and Precision-Recall curves
sscurves <- evalmod(scores = P10N10$scores, labels = P10N10$labels)

## Shows AUCs
auc(sscurves)


##################################################
### Multiple models & single test dataset
###

## Create sample datasets with 100 positives and 100 negatives
samps <- create_sim_samples(1, 100, 100, "all")
mdat <- mmdata(samps[["scores"]], samps[["labels"]],
  modnames = samps[["modnames"]]
)

## Generate an mscurve object that contains ROC and Precision-Recall curves
mscurves <- evalmod(mdat)

## Shows AUCs
auc(mscurves)


##################################################
### Single model & multiple test datasets
###

## Create sample datasets with 100 positives and 100 negatives
samps <- create_sim_samples(4, 100, 100, "good_er")
mdat <- mmdata(samps[["scores"]], samps[["labels"]],
  modnames = samps[["modnames"]],
  dsids = samps[["dsids"]]
)

## Generate an smcurve object that contains ROC and Precision-Recall curves
smcurves <- evalmod(mdat, raw_curves = TRUE)

## Get AUCs
sm_aucs <- auc(smcurves)

## Shows AUCs
sm_aucs

## Get AUCs of Precision-Recall
sm_aucs_prc <- subset(sm_aucs, curvetypes == "PRC")

## Shows AUCs
sm_aucs_prc

##################################################
### Multiple models & multiple test datasets
###

## Create sample datasets with 100 positives and 100 negatives
samps <- create_sim_samples(4, 100, 100, "all")
mdat <- mmdata(samps[["scores"]], samps[["labels"]],
  modnames = samps[["modnames"]],
  dsids = samps[["dsids"]]
)

## Generate an mscurve object that contains ROC and Precision-Recall curves
mmcurves <- evalmod(mdat, raw_curves = TRUE)

## Get AUCs
mm_aucs <- auc(mmcurves)

## Shows AUCs
mm_aucs

## Get AUCs of Precision-Recall
mm_aucs_prc <- subset(mm_aucs, curvetypes == "PRC")

## Shows AUCs
mm_aucs_prc