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Analyze the consequences and resolution when a machine learning metric optimizes the wrong objective.
Question: Explain what happens when a machine learning evaluation metric measures something other than what a project needs to optimize, and describe the action that must be taken to resolve this issue.
Sample answer: When a metric measures something other than the project's actual goals, it can no longer be trusted to select the best algorithm for the project. Because the metric is guiding the team toward the wrong objective, the team must change evaluation metrics to one that accurately reflects the project's needs.
Key points:
- The metric measures something other than the project's optimization needs.
- The team can no longer trust the metric to pick the best algorithm.
- The correct resolution is to change the evaluation metrics.
Rubric: The response should clearly identify that (1) the metric ceases to align with project needs, (2) the metric cannot be trusted to pick the best algorithm, and (3) the correct action is to change the evaluation metric.
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