Mapie

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* Fix issue 525 in contribution guidelines with syntax errors in hyperlinks and other formatting issues.
* Fix issue 495 to center correctly the prediction intervals
* Fix issue 528 to correct broken ENS image in the documentation
* Fix issue 548 to correct labels generated in tutorial
* Fix issue 547 to fix wrong warning
* Fix issue 480 (correct display of mathematical equations in generated notebooks)
* Temporary solution waiting for issue 588 to be fixed (optimize_beta not working)
* Remove several irrelevant user warnings
* Limit max sklearn version allowed at MAPIE installation
* Refactor MapieRegressor, EnsembleRegressor, and MapieQuantileRegressor, to prepare for the release of v1.0.0
* Documentation build: fix warnings, fix image generation, update sklearn version requirement
* Documentation test: add a doc testing step (in MAKEFILE and CI)
* Increase max line length from 79 to 88 characters
* Bump wheel version
* Other minor evolutions

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* Fix issue 511 to access non-conformity scores with previous path
* Update gitignore by including the documentation folder generated for Mondrian
* Fix (partially) the set-up with pip instead of conda for new contributors

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* Fix citations and license links
* Fix the CQR tutorial to have same data in both methods
* Add `** predict_params` in fit and predict method for Mapie Classifier
* Add Mondrian Conformal Prediction for regression and classification
* Add `** predict_params` in fit and predict method for Mapie Regression
* Update the ts-changepoint notebook with the tutorial
* Change import related to conformity scores into ts-changepoint notebook
* Replace `assert np.array_equal` by `np.testing.assert_array_equal` in Mapie unit tests
* Replace `github.com/simai-ml/MAPIE` by `github.com/scikit-learn-contrib/MAPIE`in all Mapie files
* Extend `ConformityScore` to support regression (with `BaseRegressionScore`) and to support classification (with `BaseClassificationScore`)
* Extend `EnsembleEstimator` to support regression (with `EnsembleRegressor`) and to support classification (with `EnsembleClassifier`)
* Refactor `MapieClassifier` by separating the handling of the `MapieClassifier` estimator into a new class called `EnsembleClassifier`
* Refactor `MapieClassifier` by separating the handling of the `MapieClassifier` conformity score into a new class called `BaseClassificationScore`
* Add severals non-conformity scores for classification (`LAC`, `APS`, `RAPS`, `TopK`) based on `BaseClassificationScore`
* Transfer the logic of classification methods into the non-conformity score classes (`LAC`, `APS`, `RAPS`, `TopK`)
* Extend the classification strategy definition by supporting `method` and `conformity_score` attributes
* Building unit tests for different `Subsample` and `BlockBooststrap` instances
* Change the sign of C_k in the `Kolmogorov-Smirnov` test documentation
* Building a training set with a fraction between 0 and 1 with `n_samples` attribute when using `split` method from `Subsample` class.

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* Fix the quantile formula to ensure valid coverage (deal with infinite interval production and asymmetric conformal scores).
* Fix sphinx dependencies

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* Issue with update from 0.8.4

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* Fix the quantile formula to ensure valid coverage for any number of calibration data in `ConformityScore`.
* Fix overloading of the value of the `method` attribute when using `MapieRegressor` and `MapieTimeSeriesRegressor`.
* Fix conda versionning.
* Reduce precision for test in `MapieCalibrator`.
* Fix invalid certificate when downloading data.
* Add citations utility to the documentation.
* Add documentation for metrics.
* Add explanation and example for symmetry argument in CQR.