plot_precision_recall_curve()

Plots a Precision-Recall curve from pre-computed performance data.

Usage

Source

plot_precision_recall_curve(
    performance_data,
    stratified_by=["probability_threshold"],
    size=600,
    renderer="plotly"
)

This function is useful when you have already computed the performance metrics and want to generate a Precision-Recall plot directly. Pre-computed data does not encode separate model identity, so canonical browser rendering treats each reference_group as a population with unknown model identity.

Parameters

performance_data: pl.DataFrame

A Polars DataFrame with the necessary performance metrics, including precision (ppv) and recall (sensitivity), along with the production prevalence quantities real_positives and n.

stratified_by: Sequence[str] = ["probability_threshold"]


The columns in performance_data used for stratification. Defaults to ["probability_threshold"].

size: int = 600

The width and height of the plot in pixels. Defaults to 600.

renderer: (plotly, browser, rtichoke_viz) = "plotly"

Rendering backend. "plotly" remains the default.

Returns

Figure or RtichokeBrowserChart

A Plotly Figure or canonical offline browser chart.