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.

Package details

AuthorAli Hamza [aut, cre]
MaintainerAli Hamza <ahamza.msse25mcs@student.nust.edu.pk>
LicenseMIT + file LICENSE
Version0.1.0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("TrustworthyMLR")

Try the TrustworthyMLR package in your browser

Any scripts or data that you put into this service are public.

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