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TrustworthyMLR  

Stability and Robustness Evaluation for Machine Learning Models
View on CRAN: Click here


Download and install TrustworthyMLR package within the R console
Install from CRAN:
install.packages("TrustworthyMLR")

Install from Github:
library("remotes")
install_github("cran/TrustworthyMLR")

Install by package version:
library("remotes")
install_version("TrustworthyMLR", "0.1.0")



Attach the package and use:
library("TrustworthyMLR")
Maintained by
Ali Hamza
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-02-20
Latest Update: 2026-02-20
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.
How to cite:
Ali Hamza (2026). TrustworthyMLR: Stability and Robustness Evaluation for Machine Learning Models. R package version 0.1.0, https://cran.r-project.org/web/packages/TrustworthyMLR. Accessed 04 Oct. 2026.
Previous versions and publish date:
No previous versions
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Complete documentation for TrustworthyMLR
Functions, R codes and Examples using the TrustworthyMLR R package
Full TrustworthyMLR package functions and examples
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