Certainty-Validity: A Diagnostic Framework for Discrete Commitment Systems
Abstract
The following includes the paper for the Certainty-Validity (CVS / CyVy) evaluation metric for datasets. CyVy helps with ML research by allowing to guide the model towards being confidentally correct and minimize confidentally inaccurate. In the repository are the following: "certainty_validity.py", a python script that allows for using the evaluation metric. "Certainty-Validity: A Diagnostic Framework for Discrete Commitment Systems", the main working paper for this. "cvs-supplementary-data.zip", a zip file that contains the a full 30 epoch benchmark in progress and epochs, with an additional figure of the isolated phase diagram that is at exists at the bottom of the paper.
Fields of Study & Subjects
Machine Learning and Data Classification
Adversarial Robustness in Machine Learning
Advanced Neural Network Applications
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 9 February 2026
- Document type
- Preprint