Performance Tables & Summary Reports

In addition to interactive curves, rtichoke generates structured, interactive performance tables and comprehensive HTML summary reports.

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Interactive Performance Tables

rtichoke performance tables summarize threshold-specific confusion matrix metrics (Sensitivity, Specificity, PPV, NPV, FPR, FNR, Accuracy, Net Benefit) across probability cutoffs.

One-Step Table Creation (create_performance_table)

library(rtichoke)

create_performance_table(
  probs = list(
    "Good Model" = example_dat$estimated_probabilities,
    "Bad Model"  = example_dat$bad_model
  ),
  reals = list(example_dat$outcome)
)

Rendering Table from Prepared Data (render_performance_table)

When performance data has already been prepared with prepare_performance_data(), use render_performance_table():

perf_data <- prepare_performance_data(
  probs = list(
    "Good Model" = example_dat$estimated_probabilities,
    "Bad Model"  = example_dat$bad_model
  ),
  reals = list(example_dat$outcome)
)

render_performance_table(perf_data)

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Comprehensive HTML Summary Reports

create_summary_report() bundles all rtichoke interactive visualizations (ROC, Precision-Recall, Gains, Lift, Decision Curve, Calibration Curve, and Performance Tables) into a single, self-contained HTML file.

create_summary_report(
  probs = list("Primary Model" = example_dat$estimated_probabilities),
  reals = list(example_dat$outcome),
  file_path = "model_performance_report.html"
)

This report is ideal for sharing comprehensive model evaluation results with collaborators, clinical stakeholders, or model validation review boards.