figure_dia: Plot Diagnostic Model Evaluation Figures

In E2E: Ensemble Learning Framework for Diagnostic and Prognostic Modeling

Plot Diagnostic Model Evaluation Figures

Description

Generates and returns a ggplot object for Receiver Operating Characteristic (ROC) curves, Precision-Recall (PRC) curves, or confusion matrices.

Usage

figure_dia(type, data, file = NULL)

Arguments

type	String, specifies the type of plot to generate. Options are "roc", "prc", or "matrix".
data	A list object containing model evaluation results. It must include: sample_score: A data frame with "label" (0/1) and "score" columns. evaluation_metrics: A list with a "Final_Threshold" or "Final_Threshold" value.
file	Optional. A string specifying the path to save the plot (e.g., "plot.png"). If NULL (the default), the plot object is returned instead of being saved.

Value

A ggplot object. If the file argument is provided, the plot is also saved to the specified path.

Examples

# Create example data for a diagnostic model
external_eval_example_dia <- list(
  sample_score = data.frame(
    ID = paste0("S", 1:100),
    label = sample(c(0, 1), 100, replace = TRUE),
    score = runif(100, 0, 1)
  ),
  evaluation_metrics = list(
    Final_Threshold = 0.53
  )
)

# Generate an ROC curve plot object
roc_plot <- figure_dia(type = "roc", data = external_eval_example_dia)
# To display the plot, simply run:
# print(roc_plot)

# Generate a PRC curve and save it to a temporary file
# tempfile() creates a safe, temporary path as required by CRAN
temp_prc_path <- tempfile(fileext = ".png")
figure_dia(type = "prc", data = external_eval_example_dia, file = temp_prc_path)

# Generate a Confusion Matrix plot
matrix_plot <- figure_dia(type = "matrix", data = external_eval_example_dia)

E2E documentation built on Aug. 27, 2025, 1:09 a.m.