limen.calibration

Calibrate model probabilities and choose decision thresholds inside manifest-driven experiments.

Canonical docs

• Calibration
• Experiment Manifest
• Reference Architecture

What this package owns

Owns probability calibration, threshold optimization, and the runtime pipeline that applies those steps to model outputs. Does not own target construction, scaler fitting, model training, or downstream trade decisioning.

Key entry points

Entry point	Use case	Notes
CalibratorProtocol, ThresholdOptimizerProtocol	Callable contracts for custom calibration or threshold functions	Used by manifest calibration wiring and pipeline helpers.
fit_calibrator	Fit the configured calibrator and threshold on validation data	Returns the fitted predictor, selected threshold, and validation score.
apply_calibrated_predict	Apply calibration and thresholding to test predictions	Returns _preds, _probs, optimal_threshold, and val_score.
sklearn_probability_calibrator	Scikit-learn probability calibration	Supports isotonic and sigmoid calibration.
grid_threshold_optimizer	Threshold optimizer over calibrated or raw probabilities	Produces the decision cutoff used for binary predictions.

Adjacent modules

• limen.experiment.manifest_core wires calibration into manifest execution.
• limen.sfd.reference_architecture consumes calibrated probabilities during evaluation.
• limen.targets creates the supervised labels that calibration evaluates against.

Quick orientation

calibration/
|-- pipeline.py     # protocol types, fit step, and calibrated prediction helper
|-- probability.py  # scikit-learn probability calibrator wrapper
`-- threshold.py    # grid threshold optimizer

Things to know

• Calibration is configured on a manifest and resolved per experiment round.
• Probability calibration and threshold optimization can be enabled independently.
• Validation data is the fitting surface for calibrators and threshold choice.
• predict() and evaluate() have different result-schema guarantees; see the canonical Calibration page before changing output fields.

Read next

• Calibration
• Experiment Manifest