You have produced findings from a predictive model, and stakeholders want to know whether they can trust the results. You need to explain how you validate model performance, check that the findings are stable, and confirm that the reported results are not driven by a single split or a misleading metric.
How do you ensure the accuracy and reliability of your data findings?
Choosing the right evaluation metrics instead of relying on accuracy aloneUsing confusion matrix analysis to connect errors to business impactUsing cross-validation to assess stability and repeatabilityExplaining reliability in a way stakeholders can trust