TrustworthyMLR: Stability and Robustness Evaluation for Machine Learning Models
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.
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=TrustworthyMLR
to link to this page.