Plot Confusion Matrix with Metrics — dx_plot

Creates a graphical representation of a confusion matrix from a dx object. The plot displays the counts of true positives, false negatives, true negatives, and false positives. Additionally, it annotates the plot with relevant performance metrics such as Sensitivity, Specificity, PPV, and NPV, along with their confidence intervals where applicable.

Usage

dx_plot_cm(dx_obj, palette = c("#e5eef7", "#0057B8"), levels = c("-", "+"))

Arguments

dx_obj: An object of class "dx" containing the diagnostic measurements.
palette: A character vector of length 2 specifying the colors for the low and high ends of the fill gradient used in the plot. Defaults to c("#e5eef7", "#0057B8").
levels: A character vector of length 2 specifying the labels for negative and positive classes, respectively. Defaults to c("-", "+").

Value

A ggplot object that represents the confusion matrix with additional performance metrics.

Examples

dx_obj <- dx(
  data = dx_heart_failure,
  true_varname = "truth",
  pred_varname = "predicted",
  outcome_label = "Heart Attack",
  setthreshold = .3
)
dx_plot_cm(dx_obj)