Which ONE of the following is NOT likely to cause a data-quality issue affecting a single ML model?
Data quality concerns the integrity of model input data, including issues such as missing, incorrectly typed, or out-of-range values. Hardware, sensor, and security failures can compromise those inputs. Incorrect weights are model parameters that affect how a model processes inputs and generates outputs, so they are a model-performance issue rather than an input-data-quality issue.
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