Learn R Programming

xpose.xtras (version 0.1.2)

ind_roc: Individual ROC plots

Description

To identify any individual likelihood predictions that may be more influential or unusual.

Note this function may have a long runtime.

Usage

ind_roc(
  xpdb,
  mapping = NULL,
  cutpoint = 1,
  type = "ca",
  title = "Individual ROC curves | @run",
  subtitle = "Ofv: @ofv, Eps shrink: @epsshk",
  caption = "@dir | Page @page of @lastpage",
  tag = NULL,
  facets,
  .problem,
  quiet,
  ...
)

Value

The desired plot

Arguments

xpdb

<xp_xtras> or <xpose_data> object

mapping

ggplot2 style mapping

cutpoint

<numeric> Of defined probabilities, which one to use in plots.

type

See Details.

title

Plot title

subtitle

Plot subtitle

caption

Plot caption

tag

Plot tag

facets

Additional facets

.problem

Problem number

quiet

Silence extra debugging output

...

Any additional aesthetics.

Details

For type-based customization of plots:

  • c ROC curve (using geom_path)

  • k Key points on ROC curve (where on curve the threshold is thres_fixed) (using geom_point)

  • p ROC space points (using geom_point)

  • t ROC space text (using geom_text)

  • a AUC in bottom right (using geom_label)

Examples

Run this code
if (FALSE) {
vismo_pomod  %>%
  set_var_types(.problem=1, catdv=DV, dvprobs=matches("^P\\d+$")) %>%
  set_dv_probs(.problem=1, 0~P0,1~P1,ge(2)~P23) %>%
  ind_roc()
}

Run the code above in your browser using DataLab