qroc-qprc {qwraps2}

Receiver-Operator and Precision-Recall Curves

Description

Construction of ROC and PRC data and plots.

Usage

qroc(x, ...)

## Default S3 method:
qroc(x, ...)

## S3 method for class 'qwraps2_confusion_matrix'
qroc(x, ...)

## S3 method for class 'glm'
qroc(x, ...)

qprc(x, ...)

## Default S3 method:
qprc(x, ...)

## S3 method for class 'qwraps2_confusion_matrix'
qprc(x, ...)

## S3 method for class 'glm'
qprc(x, ...)

Arguments

x

an object

...

pass through

Details

The area under the curve (AUC) is determined by a trapezoid approximation for both the AUROC and AUPRC.

More details and examples for graphics within qwraps2 are in the vignette(“qwraps2-graphics”, package = “qwraps2”)

Value

a ggplot. Minimal aesthetics have been used so that the user may modify the graphic as desired with ease.

Examples

#########################################################
# Example 1

df <-
  data.frame(
      truth = c(1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0)
    , pred  = c(1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0)
  )

cm <- confusion_matrix(df$truth, df$pred)
qroc(cm)
qprc(cm)

#########################################################
# Getting a ROC or PRC plot from a glm object:

mod <- glm(
  formula = spam ~ word_freq_our + word_freq_over + capital_run_length_total
, data = spambase
, family = binomial()
)

qroc(mod)
qprc(mod)

#########################################################
# View the vignette for more examples
## Not run: 
vignette("qwraps2-graphics")

## End(Not run)