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0.4.2 (2022-09-02)

  • Add tutorial for time series
  • Convert existing tutorials in .py
  • Add prefit method for CQR
  • Add tutorial for CQR

0.4.1 (2022-06-27)

  • Add packaging library in requirements
  • Fix displaying problem in pypi

0.4.0 (2022-06-24)

  • Relax and fix typing
  • Add Split Conformal Quantile Regression
  • Add EnbPI method for Time Series Regression
  • Add EnbPI Documentation
  • Add example with heteroscedastic data
  • Add ConformityScore class that allows the user to define custom conformity scores

0.3.2 (2022-03-11)

  • Refactorize unit tests
  • Add "naive" and "top-k" methods in MapieClassifier
  • Include J+aB method in regression tutorial
  • Add MNIST example for classification
  • Add cross-conformal for classification
  • Add notebooks folder containing notebooks used for generating documentation tutorials
  • Uniformize the use of matrix k_ and add an argument "ensemble" to method "predict" in regression.py
  • Add replication of the Chen Xu's tutorial testing Jackknife+aB vs Jackknife+
  • Add Jackknife+-after-Bootstrap documentation
  • Improve scikit-learn pipelines compatibility

0.3.1 (2021-11-19)

  • Add Jackknife+-after-Bootstrap method and add mean and median as aggregation functions
  • Add "cumulative_score" method in MapieClassifier
  • Allow image as input in MapieClassifier

0.3.0 (2021-09-10)

  • Renaming estimators.py module to regression.py
  • New classification.py module with MapieClassifier class, that estimates prediction sets from softmax score
  • New set of unit tests for classification.py module
  • Modification of the documentation architecture
  • Split example gallery into separate regression and classification galleries
  • Add first classification examples
  • Add method classification_coverage_score in the module metrics.py
  • Fixed code error for plotting of interval widths in tutorial of documentation
  • Added missing import statements in tutorial of documentation
  • Refactorize tests of n_jobs and verbose in utils.py

0.2.3 (2021-07-09)

  • Inclusion in conda-forge with updated release checklist
  • Add time series example
  • Add epistemic uncertainty example
  • Remove CicleCI redundancy with ReadTheDocs
  • Remove Pep8speaks
  • Include linting in CI/CD
  • Use PyPa github actions for releases

0.2.2 (2021-06-10)

  • Set alpha parameter as predict argument, with None as default value
  • Switch to github actions for continuous integration of the code
  • Add image explaining MAPIE internals on the README

0.2.1 (2021-06-04)

  • Add cv="prefit" option
  • Add sample_weight argument in fit method

0.2.0 (2021-05-21)

  • Add n_jobs argument using joblib parallel processing
  • Allow cv to take the value -1 equivalently to LeaveOneOut()
  • Introduce the cv parameter to get closer to scikit-learn API
  • Remove the n_splits, shuffle and random_state parameters
  • Simplify the method parameter
  • Fix typos in documentation and add methods descriptions in sphinx
  • Accept alpha parameter as a list or np.ndarray. If alpha is an Iterable, .predict() returns a np.ndarray of shape (n_samples, 3, len(alpha)).

0.1.4 (2021-05-07)

  • Move all alpha related operations to predict
  • Assume default LinearRegression if estimator is None
  • Improve documentation
  • return_pred argument is now ensemble boolean

0.1.3 (2021-04-30)

  • Update PyPi homepage
  • Set up publication workflows as a github action
  • Update issue and pull request templates
  • Increase sklearn compatibility (coverage_score and unit tests)

0.1.2 (2021-04-27)

  • First release on PyPi

0.1.1 (2021-04-27)

  • First release on TestPyPi

0.1.0 (2021-04-27)

  • Implement metrics.coverage
  • Implement estimators.MapieRegressor