What you will learn
- Avoid labels using future data
- Measure transition delay
- Test misclassification costs
- Plan behavior in an unrecognized regime
Avoid labels using future data
Avoid definitions that use future returns, eventual extremes or later revised data. A label must have an availability timestamp. Otherwise the apparent benefit can come from knowing the answer in advance.
Measure transition delay
Measure transition delay between a relevant change and the model's response under a stated definition. Delay is part of implementation, not an inconvenience to remove retrospectively from the test.
Test misclassification costs
Misclassification costs need not be symmetric. Applying a high-turnover strategy in an unsuitable state may be more costly than missing an eligible trade. Choose evaluation measures that reflect the actual decision consequences.
Plan behavior in an unrecognized regime
An unrecognized regime requires a defined response such as withholding dependent entries or using a conservative baseline. The response should be tested; simply adding a new label after an extreme event does not validate it prospectively.
Worked example
A classifier has high overall accuracy because one class dominates, but repeatedly makes the most costly error in a rare state. Accuracy alone can hide the decision problem.
Try it yourself
Propose an evaluation table that includes class frequency, error type and economic consequences, without selecting weights after seeing the preferred model.
Show the worked solution
Report a confusion table, per-class sample sizes, predefined decision costs and net policy results including transitions. Disclose uncertainty in rare states and retain an independent evaluation period.
Apply this to your course project
Evaluate a fixed regime policy without hindsight relabelling.
Keep the calculation inputs, assumptions and decisions with your work. Practical exercises are self-reviewed; the scored knowledge checks assess the questions shown, not an independent certification of practical competence.