API Reference¶

Complete API documentation for MAPIE v1.

Regression ¶

Class	Description
`SplitConformalRegressor`	Split conformal prediction for regression
`CrossConformalRegressor`	Cross-conformal prediction for regression
`JackknifeAfterBootstrapRegressor`	Jackknife+-after-bootstrap for regression
`ConformalizedQuantileRegressor`	Conformalized quantile regression
`TimeSeriesRegressor`	Conformal prediction for time series

Function	Description
`regression_coverage_score`	Fraction of outcomes within prediction intervals
`regression_mean_width_score`	Average width of prediction intervals
`regression_ssc`	Size-stratified coverage for regression
`regression_ssc_score`	Size-stratified coverage score
`hsic`	Hilbert-Schmidt Independence Criterion
`coverage_width_based`	Coverage width-based criterion
`regression_mwi_score`	Mean Winkler Interval score

Class	Description
`BaseRegressionScore`	Base class for regression conformity scores
`AbsoluteConformityScore`	Absolute residual conformity score
`GammaConformityScore`	Gamma (normalized) conformity score
`ResidualNormalisedScore`	Residual normalized conformity score

Class	Description
`BlockBootstrap`	Block bootstrap for time series
`Subsample`	Subsample for jackknife-after-bootstrap

Class	Description
`SplitConformalClassifier`	Split conformal prediction for classification
`CrossConformalClassifier`	Cross-conformal prediction for classification

Function	Description
`classification_coverage_score`	Fraction of true labels in prediction sets
`classification_mean_width_score`	Average size of prediction sets
`classification_ssc`	Size-stratified coverage for classification
`classification_ssc_score`	Size-stratified coverage score

Class	Description
`BaseClassificationScore`	Base class for classification scores
`NaiveConformityScore`	Naive conformity score
`LACConformityScore`	Least Ambiguous Classifier score
`APSConformityScore`	Adaptive Prediction Sets score
`RAPSConformityScore`	Regularized APS score
`TopKConformityScore`	Top-K conformity score

Class	Description
`MultiLabelClassificationController`	Risk control for multi-label classification
`BinaryClassificationController`	Risk control for binary classification
`SemanticSegmentationController`	Risk control for semantic segmentation
`BinaryClassificationRisk`	Binary classification risk utilities

Class	Description
`TopLabelCalibrator`	Top-label calibration for multi-class
`VennAbersCalibrator`	Venn-Abers calibration

Function	Description
`expected_calibration_error`	ECE metric
`top_label_ece`	Top-label ECE for multi-class
`kolmogorov_smirnov_statistic`	KS statistic
`kolmogorov_smirnov_p_value`	KS p-value
`kuiper_statistic`	Kuiper statistic
`kuiper_p_value`	Kuiper p-value
`spiegelhalter_statistic`	Spiegelhalter statistic
`spiegelhalter_p_value`	Spiegelhalter p-value

Item	Description
`train_conformalize_test_split`	Split data into train, conformalize, and test sets
`Subsample`	Subsample for jackknife-after-bootstrap
`BlockBootstrap`	Block bootstrap for time series