Merge branch 'scikit-learn-contrib:master' into master

Author: RudrakshTuwani

.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.3.1
+current_version = 0.3.2
 commit = True
 tag = True
 

.github/PULL_REQUEST_TEMPLATE.md

@@ -20,7 +20,7 @@ Please describe the tests that you ran to verify your changes. Provide instructi
 - [ ] Test A
 - [ ] Test B
 
-# Checklist:
+# Checklist
 
 - [ ] I have read the [contributing guidelines](https://github.com/simai-ml/MAPIE/blob/master/CONTRIBUTING.rst)
 - [ ] I have updated the [HISTORY.rst](https://github.com/simai-ml/MAPIE/blob/master/HISTORY.rst) and [AUTHORS.rst](https://github.com/simai-ml/MAPIE/blob/master/AUTHORS.rst) files

.gitignore

@@ -67,6 +67,9 @@ coverage.xml
 doc/_build/
 doc/generated/
 
+# Notebooks checkpoints
+**.ipynb_checkpoints
+
 # PyBuilder
 target/
 
@@ -76,3 +79,6 @@ target/
 # Images
 *.png
 *.jpeg
+
+# ZIP files
+*.zip

HISTORY.rst

@@ -2,12 +2,18 @@
 History
 =======
 
-0.3.2 (2021-XX-XX)
+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)
 ------------------

Makefile

@@ -12,7 +12,6 @@ coverage:
 	pytest -vs --doctest-modules --cov-branch --cov=mapie --cov-report term-missing --pyargs mapie
 
 doc:
-	$(MAKE) clean -C doc
 	$(MAKE) html -C doc
 
 build:

README.rst

@@ -38,10 +38,14 @@
 MAPIE - Model Agnostic Prediction Interval Estimator
 ====================================================
 
-**MAPIE** allows you to easily estimate prediction intervals (or prediction sets) using your favourite scikit-learn-compatible model for
+**MAPIE** allows you to easily estimate prediction intervals (or prediction sets)
+using your favourite scikit-learn-compatible model for
 single-output regression or multi-class classification settings.
 
-Prediction intervals output by **MAPIE** encompass both aleatoric and epistemic uncertainties and are backed by strong theoretical guarantees [1-5].
+Prediction intervals output by **MAPIE** encompass both aleatoric and epistemic
+uncertainties and are backed by strong theoretical guarantees thanks to conformal
+prediction methods [1-5].
+
 
 🔗 Requirements
 ===============

doc/api.rst

@@ -31,4 +31,6 @@ Metrics
 
    metrics.regression_coverage_score
    metrics.classification_coverage_score
+   metrics.regression_mean_width_score
+   metrics.classification_mean_width_score
 

doc/conf.py

@@ -12,8 +12,8 @@
 # All configuration values have a default; values that are commented out
 # serve to show the default.
 
-import sys
 import os
+import sys
 
 import sphinx_gallery
 import sphinx_rtd_theme
@@ -48,9 +48,11 @@
 # see https://github.com/numpy/numpydoc/issues/69
 numpydoc_show_class_members = False
 
+from distutils.version import LooseVersion
+
 # pngmath / imgmath compatibility layer for different sphinx versions
 import sphinx
-from distutils.version import LooseVersion
+
 if LooseVersion(sphinx.__version__) < LooseVersion("1.4"):
     extensions.append("sphinx.ext.pngmath")
 else:
@@ -78,14 +80,14 @@
 
 # General information about the project.
 project = u"MAPIE"
-copyright = u"2021, Quantmetry"
+copyright = u"2022, Quantmetry"
 
 # The version info for the project you"re documenting, acts as replacement for
 # |version| and |release|, also used in various other places throughout the
 # built documents.
 #
 # The short X.Y version.
-version = "0.3.1"
+version = "0.3.2"
 # The full version, including alpha/beta/rc tags.
 release = version
 
@@ -221,10 +223,8 @@
 latex_elements = {
     # The paper size ("letterpaper" or "a4paper").
     # "papersize": "letterpaper",
-
     # The font size ("10pt", "11pt" or "12pt").
     # "pointsize": "10pt",
-
     # Additional stuff for the LaTeX preamble.
     # "preamble": "",
 }
@@ -261,9 +261,7 @@
 
 # One entry per manual page. List of tuples
 # (source start file, name, description, authors, manual section).
-man_pages = [
-    ("index", "mapie", u"MAPIE Documentation", [u"Quantmetry"], 1)
-]
+man_pages = [("index", "mapie", u"MAPIE Documentation", [u"Quantmetry"], 1)]
 
 # If true, show URL addresses after external links.
 # man_show_urls = False
@@ -282,7 +280,7 @@
         u"Quantmetry",
         "MAPIE",
         "One line description of project.",
-        "Miscellaneous"
+        "Miscellaneous",
     ),
 ]
 
@@ -302,20 +300,22 @@
 # Example configuration for intersphinx: refer to the Python standard library.
 # intersphinx configuration
 intersphinx_mapping = {
-    "python": ("https://docs.python.org/{.major}".format(sys.version_info), None),
+    "python": (
+        "https://docs.python.org/{.major}".format(sys.version_info),
+        None,
+    ),
     "numpy": ("https://docs.scipy.org/doc/numpy/", None),
     "matplotlib": ("https://matplotlib.org/", None),
-    "sklearn": ("http://scikit-learn.org/stable", None)
+    "sklearn": ("http://scikit-learn.org/stable", None),
 }
 
 # sphinx-gallery configuration
 sphinx_gallery_conf = {
-    'examples_dirs': ['../examples/regression', '../examples/classification'],
-    'gallery_dirs': ['examples_regression', 'examples_classification'],
+    "examples_dirs": ["../examples/regression", "../examples/classification"],
+    "gallery_dirs": ["examples_regression", "examples_classification"],
     "doc_module": "mapie",
     "backreferences_dir": os.path.join("generated"),
-    "reference_url": {
-        "mapie": None}
+    "reference_url": {"mapie": None},
 }
 
 

doc/images/comp-methods.csv

@@ -1,4 +1,4 @@
-**Method**,**Theoretical coverage**,**Typical coverage**,**Training cost**,**Evaluation cost**
+**Method**,**Theoretical coverage**,**Typical coverage**,**Training cost**,**Evaluation cost**
 **Naïve**,No guarantee,:math:`< 1-\alpha`,1,:math:`n_{test}`
 **Jackknife**,No guarantee,:math:`\simeq 1-\alpha`,:math:`n`,:math:`n_{test}`
 ,, or :math:`< 1-\alpha` if :math:`\hat{\mu}` unstable,,
@@ -7,4 +7,6 @@
 **CV**,No guarantee,:math:`\simeq 1-\alpha`,:math:`K`,:math:`n_{test}`
 ,, or :math:`< 1-\alpha` if :math:`\hat{\mu}` unstable,,
 **CV+**,:math:`\geq 1-2\alpha`,:math:`\gtrsim 1-\alpha`,:math:`K`,:math:`K \times n_{test}`
-**CV-minmax**,:math:`\geq 1-\alpha`,:math:`> 1-\alpha`,:math:`K`,:math:`K \times n_{test}`
+**CV-minmax**,:math:`\geq 1-\alpha`,:math:`> 1-\alpha`,:math:`K`,:math:`K \times n_{test}`
+**Jackknife-aB+**,:math:`\geq 1-2\alpha`,:math:`\gtrsim 1-\alpha`,:math:`K`,:math:`K \times n_{test}`
+**Jackknife-aB-minmax**,:math:`\geq 1-\alpha`,:math:`> 1-\alpha`,:math:`K`,:math:`K \times n_{test}`