Defensive hyperparameters#60
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Pull request overview
This PR adjusts classification defaults toward more conservative XGBoost training and expands diagnostic plotting workflows.
Changes:
- Updates default classification hyperparameters.
- Adds batch plotting support for training-evaluation curves.
- Adds optional single-energy-bin plotting for classification performance metrics.
Reviewed changes
Copilot reviewed 5 out of 5 changed files in this pull request and generated 5 comments.
Show a summary per file
| File | Description |
|---|---|
src/eventdisplay_ml/hyper_parameters.py |
Updates classification XGBoost defaults. |
src/eventdisplay_ml/scripts/plot_training_evaluation.py |
Adds --model_dir batch mode and output directory handling. |
src/eventdisplay_ml/scripts/plot_classification_performance_metrics.py |
Adds --energy-bin filtering. |
README.md |
Documents training-evaluation batch plotting usage. |
docs/changes/60.feature.md |
Adds a changelog fragment for the hyperparameter update. |
Comments suppressed due to low confidence (1)
src/eventdisplay_ml/scripts/plot_training_evaluation.py:137
- This help string exceeds the repository's configured 100-character line length (see
pyproject.tomlline 88). Please wrap it to keep the CLI definitions consistent with the rest of the codebase.
help="Path to save the output plot (PNG/PDF). If not provided, display interactively. Only for single file mode.",
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
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