Metrics Helper Functions¶

The metrics module provides convenient helper functions for calculating statistical metrics. These functions provide a simple, direct interface for interactive use.

All metric implementations are internal - users should only use these helper functions.

Available Metrics¶

Accuracy Metrics¶

default_accuracy() - Calculate default accuracy for binary classification models
ead_accuracy() - Calculate Exposure at Default (EAD) accuracy
hosmer_lemeshow() - Perform Hosmer-Lemeshow goodness-of-fit test
jeffreys_test() - Perform Jeffreys Bayesian calibration test
rmse() - Calculate Root Mean Squared Error for predicted vs observed values

Discrimination Metrics¶

auc() - Calculate Area Under the ROC Curve
kolmogorov_smirnov() - Calculate Kolmogorov-Smirnov statistic for discrimination testing

Summary Statistics¶

mean() - Calculate mean values with optional segmentation
median() - Calculate median values with optional segmentation

Function Reference¶

metrics ¶

Metrics package - Public helper functions for statistical calculations.

This package provides the main public interface for calculating statistical metrics. All metric classes are internal implementations and should not be used directly.

Example usage

from tnp_statistic_library.metrics import default_accuracy, mean, median

result = default_accuracy(
    data=df, data_format="record",
    prob_def="prob", default="default"
)

describe ¶

describe(
    metric_type: str, data_format: str | None = None
) -> dict[str, Any]

Describe a metric's inputs and outputs.

Parameters:

Name	Type	Description	Default
`metric_type`	`str`	The metric type name (e.g., "auc").	required
`data_format`	`str \| None`	Optional format filter ("record" or "summary").	`None`

Returns:

Type	Description
`dict[str, Any]`	Dict with metric_type, data_formats, and per-format metadata.

list_metrics ¶

list_metrics() -> dict[str, list[str]]

Return metric types mapped to supported data formats.

options: show_source: false heading_level: 3 group_by_category: false members_order: source filters: - "!^*"