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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "TrustworthyMLR" in publications use:'
type: software
license: MIT
title: 'TrustworthyMLR: Stability and Robustness Evaluation for Machine Learning Models'
version: 0.1.0
doi: 10.32614/CRAN.package.TrustworthyMLR
abstract: 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.
authors:
- family-names: Hamza
  given-names: Ali
  email: ahamza.msse25mcs@student.nust.edu.pk
repository: https://ali-hamza817.r-universe.dev
commit: abb1705fa5e30cbdc8d3898c67012c33b43bd3da
date-released: '2026-02-18'
contact:
- family-names: Hamza
  given-names: Ali
  email: ahamza.msse25mcs@student.nust.edu.pk