fingerprint

Subject

Sampling, Validation and ML Diagnostics

Why This Module Exists

Quantifies behavior of fitted models beyond scalar accuracy metrics.

Mathematical Foundations

Partial Effect

$f_j(x_j)=E_{X_{-j}}[f(X)|X_j=x_j]$

Pairwise Interaction

$I_{ij}=f(x_i,x_j)-f_i(x_i)-f_j(x_j)$

Usage Examples

Rust

Create regression fingerprint

use openquant::fingerprint::RegressionModelFingerprint;

let fp = RegressionModelFingerprint::new(&model, &x);
let effects = fp.linear_effects()?;

API Reference

Rust API

• RegressionModelFingerprint
• ClassificationModelFingerprint
• Effect
• PairwiseEffect

Implementation Notes

• Compare fingerprints across retrains for drift detection.
• Use pairwise effects to detect hidden interaction risk.