featuresunverifiable
Featuresunverifiable is a term used in data governance and machine learning discussions to describe features whose existence, meaning, or measurement cannot be independently verified. Such features may arise from opaque data pipelines, proprietary metrics, or transformations applied to raw data that lack transparent documentation. The concept highlights the gap between model inputs and what can be auditable or reproducible by external parties.
In practice, unverifiable features can come from third-party data sources, automated feature engineering without provenance records,
Implications include reduced trust, difficulties in validating model performance, and increased risk of data drift or
Mitigation strategies emphasize data provenance and governance: documenting data sources, preserving raw inputs, recording transformation steps,