Version 0.5.0

• Add RAPS method for classification
• Add RAPS documentation

Version 0.4.2

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

Version 0.4.1

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

Version 0.4.0

• 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

Version 0.3.2

• 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

Version 0.3.1

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

Version 0.3.0

• 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

v0.2.3

• 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

Version 0.2.2

• 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

Version 0.2.1

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