All regression examples

Following is a collection of notebooks demonstrating how to use MAPIE.

1. Quickstart

The following examples present the main functionalities of MAPIE through basic quickstart regression problems.

Use MAPIE to plot prediction intervals

Use MAPIE to plot prediction intervals

Use MAPIE on data with gamma distribution

Use MAPIE on data with gamma distribution

Use MAPIE with a pre-trained model

Use MAPIE with a pre-trained model

Use MAPIE on data with uneven uncertainty

Use MAPIE on data with uneven uncertainty

Use MAPIE on data with constant uncertainty

Use MAPIE on data with constant uncertainty

Tutorial for time series

Tutorial for time series

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2. Advanced analysis

The following examples use MAPIE for discussing more complex MAPIE problems.

Conformal Predictive Distribution with MAPIE

Conformal Predictive Distribution with MAPIE

The symmetric_correction parameter of ConformalizedQuantileRegressor

The symmetric_correction parameter of ConformalizedQuantileRegressor

Hyperparameters tuning with CrossConformalRegressor

Hyperparameters tuning with CrossConformalRegressor

Time series: example of the EnbPI technique

Time series: example of the EnbPI technique

Estimating aleatoric and epistemic uncertainties

Estimating aleatoric and epistemic uncertainties

Focus on intervals width

Focus on intervals width

Focus on residual normalised score

Focus on residual normalised score

Focus on local (or “conditional”) coverage

Focus on local (or "conditional") coverage

ConformalizedQuantileRegressor on gamma distributed data

ConformalizedQuantileRegressor on gamma distributed data

Coverage validity of MAPIE for regression tasks

Coverage validity of MAPIE for regression tasks

Comparison between conformalized quantile regressor and cross methods

Comparison between conformalized quantile regressor and cross methods

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3. Simulations from scientific articles

The following examples reproduce the simulations from the scientific articles that introduce the methods implemented in MAPIE for regression settings.

Predictive inference with the jackknife+, Foygel-Barber et al. (2020)

Predictive inference with the jackknife+, Foygel-Barber et al. (2020)

Adaptive conformal predictions for time series, Zaffran et al. (2022)

Adaptive conformal predictions for time series, Zaffran et al. (2022)

Predictive inference is free with the Jackknife+-after-Bootstrap, Kim et al. (2020)

Predictive inference is free with the Jackknife+-after-Bootstrap, Kim et al. (2020)

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4. Other notebooks

This section lists a series of Jupyter notebooks hosted on the MAPIE Github repository that can be run on Google Colab:

• Estimating prediction intervals for time series forecast with EnbPI and ACI