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57 lines
1.4 KiB
Markdown
57 lines
1.4 KiB
Markdown
# Evaluation concepts and matching
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Evaluation is not just "run predictions and compute one number".
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The reported metric depends on the evaluation task, the matching rule, and the
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treatment of clip boundaries and generic labels.
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## Task families answer different questions
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Built-in task families include:
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- sound event detection,
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- sound event classification,
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- top-class detection,
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- clip detection,
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- clip classification.
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Choose the task that matches the scientific or engineering question.
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## Matching matters
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For sound-event-style tasks, predictions and annotations are matched using an
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affinity function.
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Important controls include:
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- `affinity`,
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- `affinity_threshold`,
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- `strict_match`,
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- `ignore_start_end`.
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Small changes here can change the reported metric without changing the
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underlying predictions.
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## Boundary handling matters
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The evaluation base task can exclude events near clip boundaries through
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`ignore_start_end`.
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This is useful when clip boundaries make matches ambiguous.
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## Generic labels can matter in classification
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Classification tasks can include or exclude generic targets depending on
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configuration.
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That affects what counts as a valid class-level comparison.
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## Related pages
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- Evaluate on a test set:
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{doc}`../tutorials/evaluate-on-a-test-set`
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- Evaluation config reference:
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{doc}`../reference/configs/evaluation/evaluation-config`
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- Model output and validation:
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{doc}`model-output-and-validation`
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