get_cutoffs_data: Prepare cutoff data for ROC curve annotation

In plotthis: High-Level Plotting Built Upon 'ggplot2' and Other Plotting Packages

Prepare cutoff data for ROC curve annotation

Description

Internal helper that computes the sensitivity and specificity values for a set of user-supplied cutoff points (or computed via OptimalCutpoints methods) across categories defined by group_by and/or facet_by columns. Used by ROCCurveAtomic() to annotate the ROC curve with cutoff markers and labels.

Usage

get_cutoffs_data(
  data,
  truth_by,
  score_by,
  cat_by,
  cutoffs_at = NULL,
  cutoffs_labels = NULL,
  cutoffs_accuracy = 0.001,
  n_cuts = 0,
  increasing = TRUE
)

Arguments

data	A data frame with the truth and score columns.
truth_by	A character string of the column name that contains the true class labels (binary, 0/1 or TRUE/FALSE).
score_by	A character string of the column name that contains the predicted scores.
cat_by	A character string of the column name to categorise/group the data. When specified, cutoffs are calculated separately for each category level, enabling per-group or per-facet cutoff annotation.
cutoffs_at	A vector of user-supplied cutoff values to plot as points. When non-NULL, overrides n_cuts. Supports both raw numeric values and method names from optimal.cutpoints.
cutoffs_labels	A character vector of user-supplied labels for the cutoffs. Must be the same length as cutoffs_at. When NULL, labels are generated automatically.
cutoffs_accuracy	A numeric value specifying the rounding precision for automatically generated cutoff labels. Default: 0.001.
n_cuts	An integer specifying the number of evenly-spaced quantile-based cutoff points. Ignored when cutoffs_at is non-NULL. Default: 0 (no quantile cutoffs).
increasing	A logical value. If TRUE (default), higher scores indicate the positive class; if FALSE, lower scores indicate the positive class.

Details

Cutoffs can be specified either as numeric values (raw score thresholds) or as method names from the OptimalCutpoints package for automatic optimal cutoff identification. When n_cuts > 0, n_cuts evenly-spaced quantile values of the score distribution are used as cutoffs.

Value

A data frame with columns cutoff, x (1 - specificity), y (sensitivity), label, and cat_by (the category name).

plotthis documentation built on July 9, 2026, 5:07 p.m.