Dataset training, validation and testing

metric

ML-R1.4-01M: Metadata includes information about the dataset used for ML model training, testing and validation. Test: 1) The dataset is mentioned and its properties are explained. 2) The breakdown of the data for the individual phases (training, testing, and validation) is explained.

Principle: R

Rationale: Information about the dataset used for training, validation and testing of an ML model is important towards the better understanding and easier reuse of an ML model. This is a disciplinary requirement.

FAIR Metrics: R1.4

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FAIR for Machine Learning Models

This rubric consists of assessment metrics that evaluate the FAIR maturity of ML models. The metrics...

FAIR machine learning model FAIR assessment NFDI4DataScience

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