Merge branch 'master' into spider

Author: MattEding

.circleci/config.yml

@@ -5,14 +5,18 @@ jobs:
     docker:
       - image: circleci/python:3.6.1
     environment:
-      - USERNAME: "scikit-learn-contrib"
-      - DOC_REPO: "imbalanced-learn"
+      - USERNAME: "glemaitre"
+      - ORGANIZATION: "imbalanced-learn"
+      - DOC_REPO: "imbalanced-learn.github.io"
       - DOC_URL: ""
       - EMAIL: "g.lemaitre58@gmail.com"
       - MINICONDA_PATH: ~/miniconda
       - CONDA_ENV_NAME: testenv
       - PYTHON_VERSION: 3
     steps:
+      - add_ssh_keys:
+          fingerprints:
+            - "34:ea:b1:d9:b1:e2:5d:79:81:c4:d0:39:ca:85:e1:ef"
       - checkout
       - run: ./build_tools/circle/checkout_merge_commit.sh
       - run: ./build_tools/circle/build_doc.sh
@@ -27,11 +31,11 @@ jobs:
       - attach_workspace:
           at: doc/_build/html
       - run: ls -ltrh doc/_build/html
-      # - deploy:
-      #     command: |
-      #       if [[ "${CIRCLE_BRANCH}" =~ ^master$|^[0-9]+\.[0-9]+\.X$ ]]; then
-      #         bash ./build_tools/circle/push_doc.sh doc/_build/html
-      #       fi
+      - deploy:
+          command: |
+            if [[ "${CIRCLE_BRANCH}" =~ ^master$|^[0-9]+\.[0-9]+\.X$ ]]; then
+              bash ./build_tools/circle/push_doc.sh doc/_build/html
+            fi
     filters:
       branches:
         ignore: gh-pages

.gitignore

@@ -118,4 +118,5 @@ cythonize.dat
 # build documentation
 doc/_build/
 doc/auto_examples/
-doc/generated/
+doc/generated/
+doc/bibtex/auto

.readthedocs.yml

@@ -1,5 +1,5 @@
 # make it explicit that we favor the new container-based travis workers
-dist: xenial
+dist: bionic
 sudo: false
 
 language: python
@@ -30,21 +30,17 @@ matrix:
   include:
     # This environment tests the using anaconda
     # Ubuntu 14.04 environment
-    - env: DISTRIB="ubuntu"
+    - env: DISTRIB="ubuntu" TEST_DOC="true" TEST_NUMPYDOC="false"
     # Latest release
-    - env: DISTRIB="conda" PYTHON_VERSION="3.6"
-           NUMPY_VERSION="*" SCIPY_VERSION="*" SKLEARN_VERSION="0.21.2"
-           OPTIONAL_DEPS="true"
     - env: DISTRIB="conda" PYTHON_VERSION="3.7"
-           NUMPY_VERSION="*" SCIPY_VERSION="*" SKLEARN_VERSION="0.21.2"
-           OPTIONAL_DEPS="false"
+           NUMPY_VERSION="*" SCIPY_VERSION="*" SKLEARN_VERSION="master"
+           OPTIONAL_DEPS="keras" TEST_DOC="true" TEST_NUMPYDOC="false"
     - env: DISTRIB="conda" PYTHON_VERSION="3.7"
            NUMPY_VERSION="*" SCIPY_VERSION="*" SKLEARN_VERSION="master"
-           OPTIONAL_DEPS="false"
-  allow_failures:
+           OPTIONAL_DEPS="tensorflow" TEST_DOC="true" TEST_NUMPYDOC="false"
     - env: DISTRIB="conda" PYTHON_VERSION="3.7"
            NUMPY_VERSION="*" SCIPY_VERSION="*" SKLEARN_VERSION="master"
-           OPTIONAL_DEPS="false"
+           OPTIONAL_DEPS="false" TEST_DOC="false" TEST_NUMPYDOC="true"
 
 install: source build_tools/travis/install.sh
 script: bash build_tools/travis/test_script.sh

.travis.yml

@@ -4,7 +4,7 @@
 
 .. _scikit-learn-contrib: https://github.com/scikit-learn-contrib
 
-|Travis|_ |AppVeyor|_ |Codecov|_ |CircleCI|_ |ReadTheDocs|_ |PythonVersion|_ |Pypi|_ |Gitter|_
+|Travis|_ |AppVeyor|_ |Codecov|_ |CircleCI|_ |PythonVersion|_ |Pypi|_ |Gitter|_
 
 .. |Travis| image:: https://travis-ci.org/scikit-learn-contrib/imbalanced-learn.svg?branch=master
 .. _Travis: https://travis-ci.org/scikit-learn-contrib/imbalanced-learn
@@ -18,9 +18,6 @@
 .. |CircleCI| image:: https://circleci.com/gh/scikit-learn-contrib/imbalanced-learn.svg?style=shield&circle-token=:circle-token
 .. _CircleCI: https://circleci.com/gh/scikit-learn-contrib/imbalanced-learn/tree/master
 
-.. |ReadTheDocs| image:: https://readthedocs.org/projects/imbalanced-learn/badge/?version=latest
-.. _ReadTheDocs: https://imbalanced-learn.readthedocs.io/en/latest/?badge=latest
-
 .. |PythonVersion| image:: https://img.shields.io/pypi/pyversions/imbalanced-learn.svg
 .. _PythonVersion: https://img.shields.io/pypi/pyversions/imbalanced-learn.svg
 
@@ -44,7 +41,7 @@ Documentation
 Installation documentation, API documentation, and examples can be found on the
 documentation_.
 
-.. _documentation: https://imbalanced-learn.readthedocs.io/en/stable/
+.. _documentation: https://imbalanced-learn.org/stable/
 
 Installation
 ------------
@@ -153,19 +150,23 @@ Below is a list of the methods currently implemented in this module.
 * Over-sampling
     1. Random minority over-sampling with replacement
     2. SMOTE - Synthetic Minority Over-sampling Technique [8]_
-    3. bSMOTE(1 & 2) - Borderline SMOTE of types 1 and 2 [9]_
-    4. SVM SMOTE - Support Vectors SMOTE [10]_
-    5. ADASYN - Adaptive synthetic sampling approach for imbalanced learning [15]_
+    3. SMOTENC - SMOTE for Nominal Continuous [8]_
+    4. bSMOTE(1 & 2) - Borderline SMOTE of types 1 and 2 [9]_
+    5. SVM SMOTE - Support Vectors SMOTE [10]_
+    6. ADASYN - Adaptive synthetic sampling approach for imbalanced learning [15]_
+    7. KMeans-SMOTE [17]_
 
 * Over-sampling followed by under-sampling
     1. SMOTE + Tomek links [12]_
     2. SMOTE + ENN [11]_
 
 * Ensemble classifier using samplers internally
-    1. EasyEnsemble [13]_
-    2. BalanceCascade [13]_
-    3. Balanced Random Forest [16]_
-    4. Balanced Bagging
+    1. Easy Ensemble classifier [13]_
+    2. Balanced Random Forest [16]_
+    3. Balanced Bagging
+    4. RUSBoost [18]_
+
+* Mini-batch resampling for Keras and Tensorflow
 
 The different algorithms are presented in the sphinx-gallery_.
 
@@ -206,3 +207,7 @@ References:
 .. [15] : H. He, Y. Bai, E. A. Garcia, S. Li, “ADASYN: Adaptive synthetic sampling approach for imbalanced learning,” In Proceedings of the 5th IEEE International Joint Conference on Neural Networks, pp. 1322-1328, 2008.
 
 .. [16] : C. Chao, A. Liaw, and L. Breiman. "Using random forest to learn imbalanced data." University of California, Berkeley 110 (2004): 1-12.
+
+.. [17] : Felix Last, Georgios Douzas, Fernando Bacao, "Oversampling for Imbalanced Learning Based on K-Means and SMOTE"
+
+.. [18] : Seiffert, C., Khoshgoftaar, T. M., Van Hulse, J., & Napolitano, A. "RUSBoost: A hybrid approach to alleviating class imbalance." IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans 40.1 (2010): 185-197.

README.rst

@@ -10,7 +10,12 @@ environment:
     - PYTHON: "C:\\Miniconda36-x64"
       PYTHON_VERSION: "3.6"
       PYTHON_ARCH: "64"
-      OPTIONAL_DEP: "pandas keras tensorflow"
+      OPTIONAL_DEP: "pandas keras tensorflow=1"
+
+    - PYTHON: "C:\\Miniconda36-x64"
+      PYTHON_VERSION: "3.6"
+      PYTHON_ARCH: "64"
+      OPTIONAL_DEP: "pandas tensorflow"
 
     - PYTHON: "C:\\Miniconda36-x64"
       PYTHON_VERSION: "3.7"
@@ -30,8 +35,8 @@ install:
   - conda update conda -y -q
   - conda create -n testenv --yes python=%PYTHON_VERSION% pip
   - activate testenv
-  - conda install scipy numpy -y -q
-  - conda install scikit-learn -y -q
+  - conda install scipy numpy joblib -y -q
+  - pip install --pre -f https://sklearn-nightly.scdn8.secure.raxcdn.com scikit-learn
   - conda install %OPTIONAL_DEP% -y -q
   - conda install pytest pytest-cov -y -q
   - pip install codecov

appveyor.yml

@@ -74,6 +74,15 @@ fi
 
 MAKE_TARGET=html
 
+# Installing required system packages to support the rendering of math
+# notation in the HTML documentation
+sudo -E apt-get -yq update
+sudo -E apt-get -yq remove texlive-binaries --purge
+sudo -E apt-get -yq --no-install-suggests --no-install-recommends \
+    install dvipng texlive-latex-base texlive-latex-extra \
+    texlive-latex-recommended texlive-fonts-recommended \
+    latexmk gsfonts ccache
+
 # deactivate circleci virtualenv and setup a miniconda env instead
 if [[ `type -t deactivate` ]]; then
     deactivate
@@ -88,13 +97,15 @@ conda update --yes --quiet conda
 
 # Configure the conda environment and put it in the path using the
 # provided versions
-conda create -n $CONDA_ENV_NAME --yes --quiet python=3.6
+conda create -n $CONDA_ENV_NAME --yes --quiet python=3.7
 source activate $CONDA_ENV_NAME
 
-conda install --yes pip numpy scipy pillow matplotlib sphinx \
-      sphinx_rtd_theme numpydoc pandas keras
-pip install --pre scikit-learn
+conda install --yes pip numpy scipy joblib pillow matplotlib memory_profiler \
+        sphinx sphinx_rtd_theme \pandas keras tensorflow=1
+pip install --pre -f https://sklearn-nightly.scdn8.secure.raxcdn.com scikit-learn
 pip install -U git+https://github.com/sphinx-gallery/sphinx-gallery.git
+pip install -U git+https://github.com/numpy/numpydoc.git
+pip install -U git+https://github.com/mcmtroffaes/sphinxcontrib-bibtex.git
 
 # Build and install imbalanced-learn in dev mode
 ls -l

build_tools/circle/build_doc.sh

@@ -27,13 +27,13 @@ MSG="Pushing the docs to $dir/ for branch: $CIRCLE_BRANCH, commit $CIRCLE_SHA1"
 
 cd $HOME
 if [ ! -d $DOC_REPO ];
-then git clone --depth 1 --no-checkout -b gh-pages "git@github.com:"$USERNAME"/"$DOC_REPO".git";
+then git clone --depth 1 --no-checkout -b master "git@github.com:"$ORGANIZATION"/"$DOC_REPO".git";
 fi
 cd $DOC_REPO
 git config core.sparseCheckout true
 echo $dir > .git/info/sparse-checkout
-git checkout gh-pages
-git reset --hard origin/gh-pages
+git checkout master
+git reset --hard origin/master
 git rm -rf $dir/ && rm -rf $dir/
 cp -R $GENERATED_DOC_DIR $dir
 touch $dir/.nojekyll
@@ -42,6 +42,6 @@ git config --global user.name $USERNAME
 git config --global push.default matching
 git add -f $dir/
 git commit -m "$MSG" $dir
-git push origin gh-pages
+git push origin master
 
 echo $MSG

build_tools/circle/push_doc.sh

@@ -28,33 +28,31 @@ if [[ "$DISTRIB" == "conda" ]]; then
     MINICONDA_PATH=/home/travis/miniconda
     chmod +x miniconda.sh && ./miniconda.sh -b -p $MINICONDA_PATH
     export PATH=$MINICONDA_PATH/bin:$PATH
-    conda config --set always_yes yes --set changeps1 no
-    conda install conda=4.6
-    conda update -q conda
-    conda info -a
 
     # Configure the conda environment and put it in the path using the
     # provided versions
     conda create -n testenv --yes python=$PYTHON_VERSION pip
     source activate testenv
     conda install --yes numpy=$NUMPY_VERSION scipy=$SCIPY_VERSION
 
-    if [[ "$OPTIONAL_DEPS" == "true" ]]; then
-        conda install --yes pandas keras tensorflow
+    if [[ "$OPTIONAL_DEPS" == "keras" ]]; then
+        conda install --yes pandas keras tensorflow=1
         KERAS_BACKEND=tensorflow
         python -c "import keras.backend"
         sed -i -e 's/"backend":[[:space:]]*"[^"]*/"backend":\ "'$KERAS_BACKEND'/g' ~/.keras/keras.json;
+    elif [[ "$OPTIONAL_DEPS" == "tensorflow" ]]; then
+        conda install --yes pandas tensorflow
     fi
 
     if [[ "$SKLEARN_VERSION" == "master" ]]; then
-        conda install --yes cython
-        pip install -U git+https://github.com/scikit-learn/scikit-learn.git
+        pip install --pre -f https://sklearn-nightly.scdn8.secure.raxcdn.com scikit-learn
     else
         conda install --yes scikit-learn=$SKLEARN_VERSION
     fi
 
     conda install --yes pytest pytest-cov
     pip install codecov
+    pip install -U git+https://github.com/numpy/numpydoc.git
 
 elif [[ "$DISTRIB" == "ubuntu" ]]; then
     # At the time of writing numpy 1.9.1 is included in the travis
@@ -65,8 +63,8 @@ elif [[ "$DISTRIB" == "ubuntu" ]]; then
     virtualenv --system-site-packages --python=python3 testvenv
     source testvenv/bin/activate
 
-    pip3 install scikit-learn
-    pip3 install pandas keras tensorflow
+    pip install --pre -f https://sklearn-nightly.scdn8.secure.raxcdn.com scikit-learn
+    pip3 install pandas
     pip3 install pytest pytest-cov codecov sphinx numpydoc
 
 fi

build_tools/travis/install.sh

@@ -25,7 +25,14 @@ run_tests(){
 
     # Test doc
     cd $OLDPWD
-    make test-doc
+    if [[ "$TEST_DOC" == "true" ]]; then
+        make test-doc
+    fi
+
+    # Validate numpydoc style
+    if [[ "$TEST_NUMPYDOC" == "true" ]]; then
+        pytest -vsl maint_tools/test_docstring.py
+    fi
 }
 
 if [[ "$SKIP_TESTS" != "true" ]]; then

build_tools/travis/test_script.sh

@@ -111,10 +111,8 @@ Prototype selection
    :toctree: generated/
    :template: class.rst
 
-   ensemble.BalanceCascade
    ensemble.BalancedBaggingClassifier
    ensemble.BalancedRandomForestClassifier
-   ensemble.EasyEnsemble
    ensemble.EasyEnsembleClassifier
    ensemble.RUSBoostClassifier
 
@@ -251,5 +249,4 @@ Imbalance-learn provides some fast-prototyping tools.
 
    utils.estimator_checks.check_estimator
    utils.check_neighbors_object
-   utils.check_ratio
    utils.check_sampling_strategy