batdetect2/docs/source/how_to/tune-detection-threshold.md

How to tune detection threshold

Use this guide to compare detection outputs at different threshold values.

The goal is not to find a universal threshold.

The goal is to choose a threshold that fits your reviewed local data and the project trade-off between missed calls and false positives.

1) Start with a baseline run

Run an initial prediction workflow and keep outputs in a dedicated folder.

2) Sweep threshold values

Run predict multiple times with different thresholds (for example 0.1, 0.3, 0.5) and compare output counts and quality on the same validation subset.

batdetect2 predict directory \
  path/to/model.ckpt \
  path/to/audio_dir \
  path/to/outputs_thr_03 \
  --detection-threshold 0.3

Keep each threshold run in a separate output directory.

That makes it easier to compare counts and inspect example files without mixing results.

3) Validate against known calls

Use files with trusted annotations or expert review to select a threshold that fits your project goals.

Check both:

• obvious false positives,
• obvious missed calls.

If class interpretation matters downstream, inspect class ranking behavior as well, not just detection counts.

4) Record your chosen setting

Write down the chosen threshold and rationale so analyses are reproducible.

For conceptual trade-offs, see {doc}../explanation/model-output-and-validation.