plot.sPLSDA.auroc

Plots the cross-validated area under the ROC curve (AUC) of each class against all the others, component by component.

plot.sPLSDA.auroc(
  DEprot.sPLSDA.object,
  component = NULL,
  point.colors = NULL,
  show.sd = TRUE,
  title = "**Cross-validated AUC**"
)

Arguments

DEprot.sPLSDA.object

An object of class DEprot.sPLSDA.

component

Numeric value (or vector) indicating the component(s) to display. Default: NULL (all the components).

point.colors

Color-vector used for the components. Default: NULL (automatic colors).

show.sd

Logical value indicating whether the standard deviation over the repeats should be drawn as an error bar. Default: TRUE.

title

String indicating the title of the plot (markdown annotation supported). Default: "**Cross-validated AUC**".

Value

A ggplot object.

Details

This is the AUC computed by mixOmics::perf over the resampling, and not a ROC curve drawn on the samples used to fit the model: the latter would be optimistic by construction, since a supervised model is fitted precisely to rank those samples correctly. The dashed line at 0.5 is the value of a coin toss.

The comparisons are one class against all the others pooled, which is how mixOmics reports them for a multi-class design.

See also

perform.sPLSDA, plot.sPLSDA.performance

Author

Sebastian Gregoricchio

Examples

# \donttest{
# the performances are estimated by resampling the samples: with 12 samples in 3 groups
# the leave-one-out scheme is the only one leaving enough samples in each fold
splsda <- perform.sPLSDA(DEprot.object = DEprot::test.toolbox$dpo.imp,
                         group.column = "condition",
                         keepX = 5,
                         validate = TRUE,
                         validation = "loo")
#> Estimating the classification performances by cross-validation...

plot.sPLSDA.auroc(DEprot.sPLSDA.object = splsda)

# }