TrustworthyMLR-package: TrustworthyMLR: Stability and Robustness Evaluation for...

In TrustworthyMLR: Stability and Robustness Evaluation for Machine Learning Models

TrustworthyMLR: Stability and Robustness Evaluation for Machine Learning Models

Description

Provides tools for evaluating the trustworthiness of machine learning models in production and research settings. Computes a Stability Index that quantifies the consistency of model predictions across multiple runs or resamples, and a Robustness Score that measures model resilience under small input perturbations. Designed for data scientists, ML engineers, and researchers who need to monitor and ensure model reliability, reproducibility, and deployment readiness.

Author(s)

Maintainer: Ali Hamza [e-mail]

TrustworthyMLR documentation built on Feb. 20, 2026, 5:09 p.m.