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Add remediation steps to PredictableMetrics healthcheck (#5083) #5083

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Add remediation steps to PredictableMetrics healthcheck (#5083) #5083

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21 changes: 21 additions & 0 deletions ax/analysis/healthcheck/predictable_metrics.py
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Original file line number Diff line number Diff line change
Expand Up @@ -29,6 +29,26 @@
"be reliably predicted by the model. "
)
DEFAULT_MODEL_FIT_THRESHOLD = 0.1
INVESTIGATION_STEPS: str = (
"\n\n**Suggested next steps:**\n"
"- If the metric is noisy, increase replications per trial "
"so the averaged observation is more stable and the model "
"can detect the underlying signal.\n"
"- Run more trials so the model has enough data to learn "
"the parameter-metric relationship (leave-one-out cross-"
"validation needs sufficient training points).\n"
"- Verify that the tuned parameters actually influence this "
"metric. If the metric does not depend on any parameter, "
"the model cannot learn a relationship and predictions will "
"be no better than the mean.\n"
"- Check that the metric has sufficient variation across "
"trials. If metric values are nearly constant, the model "
"fit score will be very low or negative.\n"
"- Check for missing values, outliers, or bugs in the "
"metric implementation that could corrupt model training.\n"
"- If this metric is not critical, removing it from the "
"optimization config may simplify the problem."
)


@final
Expand Down Expand Up @@ -156,6 +176,7 @@ def compute(

if warning_message is not None:
subtitle = HEALTHCHECK_DESCRIPTION + warning_message
subtitle += INVESTIGATION_STEPS
if self.guidance_message is not None:
subtitle += "\n\n" + self.guidance_message
return create_healthcheck_analysis_card(
Expand Down