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MTN: classification examples and notebooks reorganisation (#689)
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doc/index_binary_classification.rst

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.. toctree::
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:maxdepth: 2
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examples_classification/4-tutorials/plot_main-tutorial-binary-classification
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examples_classification/2-advanced-analysis/plot_main-tutorial-binary-classification
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theoretical_description_binary_classification

doc/index_classification.rst

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:maxdepth: 2
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choosing_the_right_algorithm_classification
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examples_classification/4-tutorials/plot_main-tutorial-classification
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examples_classification/4-tutorials/plot_crossconformal
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examples_classification/index
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notebooks_classification
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theoretical_description_classification
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index_binary_classification

examples/classification/1-quickstart/plot_comp_methods_on_2d_dataset.py renamed to examples/classification/2-advanced-analysis/plot_comp_methods_on_2d_dataset.py

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"""
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======================================================
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Comparing prediction sets on a two-dimensional dataset
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LAC and APS methods explained
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======================================================
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In this tutorial, we compare the prediction sets estimated by

examples/classification/4-tutorials/plot_crossconformal.py renamed to examples/classification/2-advanced-analysis/plot_crossconformal.py

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"""
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==================================
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Cross-conformal for classification
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==================================
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=========================================
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Cross conformal classification explained
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=========================================
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In this tutorial, we estimate the impact of the
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training/conformalization split on the prediction sets and

examples/classification/4-tutorials/plot_main-tutorial-binary-classification.py renamed to examples/classification/2-advanced-analysis/plot_main-tutorial-binary-classification.py

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"""
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===========================
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Tutorial for set prediction
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===========================
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============================================================
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Set prediction example in the binary classification setting
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============================================================
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In this example, we propose set prediction for binary classification
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estimated by :class:`~mapie_v1.classification.SplitConformalClassifier` with the "lac"

examples/classification/3-scientific-articles/plot_sadinle2019_example.py

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"""
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================================================
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Reproducing Example 7 from Sadinle et al. (2019)
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=======================================================================================
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Least Ambiguous Set-Valued Classifiers with Bounded Error Levels, Sadinle et al. (2019)
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=======================================================================================
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We use :class:`~mapie_v1.classification.SplitConformalClassifier` to reproduce
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Example 7 from Sadinle et al. (2019).
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.. _classification_examples_4:
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4. Other notebooks
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--------------------
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This section lists a series of Jupyter notebooks hosted on the MAPIE Github repository that can be run on Google Colab:
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- `Deep learning with MAPIE on the Cifar10 dataset <https://github.com/scikit-learn-contrib/MAPIE/tree/master/notebooks/classification/Cifar10.ipynb>`_

examples/classification/4-tutorials/README.rst

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examples/classification/4-tutorials/plot_main-tutorial-classification.py

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examples/classification/README.rst

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.. _classification_examples:
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Classification examples
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=======================
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All classification examples
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============================
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Following is a collection of notebooks demonstrating how to use MAPIE in classification.

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