Merge branch 'realese/v0.3.0'

.github/CODE_OF_CONDUCT.md

@@ -55,7 +55,7 @@ further defined and clarified by project maintainers.
 ## Enforcement
 
 Instances of abusive, harassing, or otherwise unacceptable behavior may be
-reported by contacting the project team. All
+reported by contacting the project team at team@uplift-modeling.com. All
 complaints will be reviewed and investigated and will result in a response that
 is deemed necessary and appropriate to the circumstances. The project team is
 obligated to maintain confidentiality with regard to the reporter of an incident.

.github/CONTRIBUTING.md

@@ -19,8 +19,8 @@ So, please make a pull request to the ``dev`` branch.
 1. Fork the [project repository](https://github.com/maks-sh/scikit-uplift).
 2. Clone your fork of the scikit-uplift repo from your GitHub account to your local disk:
     ``` bash
-    $ git clone git@github.com:YourLogin/scikit-uplift.git
-    $ cd scikit-learn
+    $ git clone https://github.com/YourName/scikit-uplift
+    $ cd scikit-uplift
     ```
 3. Add the upstream remote. This saves a reference to the main scikit-uplift repository, which you can use to keep your repository synchronized with the latest changes:
     ``` bash
@@ -36,7 +36,7 @@ So, please make a pull request to the ``dev`` branch.
     $ git checkout -b feature/my_new_feature
     ```
     and start making changes. Always use a feature branch. It’s a good practice.
-6. Develop the feature on your feature branch on your computer, using Git to do the version control. When you’re done editing, add changed files using ``git add`` and then ``git commit``.
+6. Develop the feature on your feature branch on your computer, using Git to do the version control. When you’re done editing, add changed files using ``git add .`` and then ``git commit``
 Then push the changes to your GitHub account with:
 
     ``` bash
@@ -55,4 +55,4 @@ We follow the PEP8 style guide for Python. Docstrings follow google style.
 * Use the present tense ("Add feature" not "Added feature")
 * Use the imperative mood ("Move cursor to..." not "Moves cursor to...")
 * Limit the first line to 72 characters or less
-* Reference issues and pull requests liberally after the first line
+* Reference issues and pull requests liberally after the first line

.github/workflows/PyPi_upload.yml

@@ -0,0 +1,28 @@
+name: Upload to PyPi
+
+on:
+  release:
+    types: [published]
+
+jobs:
+  deploy:
+
+    runs-on: ubuntu-latest
+
+    steps:
+    - uses: actions/checkout@v2
+    - name: Set up Python
+      uses: actions/setup-python@v2
+      with:
+        python-version: '3.x'
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install setuptools wheel twine
+    - name: Build and publish
+      env:
+       TWINE_USERNAME: ${{ secrets.PYPI_USERNAME }}
+       TWINE_PASSWORD: ${{ secrets.PYPI_PASSWORD }}
+      run: |
+        python setup.py sdist bdist_wheel
+        twine upload dist/*

.github/workflows/ci-test.yml

@@ -0,0 +1,48 @@
+name: Python package
+
+on:
+  push:
+    branches: [ master ]
+  pull_request:
+
+
+jobs:
+  test:
+    name: Check tests
+    runs-on: ${{ matrix.operating-system }}
+    strategy:
+      matrix:
+        operating-system: [ubuntu-latest, windows-latest, macos-latest]
+        python-version: [3.6, 3.7, 3.8, 3.9]
+      fail-fast: false
+
+    steps:
+    - uses: actions/checkout@v2
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v2
+      with:
+        python-version: ${{ matrix.python-version }}
+    - name: Install dependencies and lints
+      run: pip install pytest .[tests]
+    - name: Run PyTest
+      run: pytest
+
+  check_sphinx_build:
+    name: Check Sphinx build for docs
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: [3.8]
+    steps:
+    - name: Checkout
+      uses: actions/checkout@v2
+    - name: Set up Python
+      uses: actions/setup-python@v2
+      with:
+        python-version: ${{ matrix.python-version }}
+    - name: Update pip
+      run: python -m pip install --upgrade pip
+    - name: Install dependencies
+      run: pip install -r docs/requirements.txt
+    - name: Run Sphinx
+      run: sphinx-build -b html docs /tmp/_docs_build

Readme.rst

@@ -36,27 +36,36 @@
 scikit-uplift
 ===============
 
-**scikit-uplift** is a Python module for classic approaches for uplift modeling built on top of scikit-learn.
+**scikit-uplift (sklift)** is an uplift modeling python package that provides fast sklearn-style models implementation, evaluation metrics and visualization tools.
 
-Uplift prediction aims to estimate the causal impact of a treatment at the individual level.
+Uplift modeling estimates a causal effect of treatment and uses it to effectively target customers that are most likely to respond to a marketing campaign.
+
+**Use cases for uplift modeling:**
+
+* Target customers in the marketing campaign. Quite useful in promotion of some popular product where there is a big part of customers who make a target action by themself without any influence. By modeling uplift you can find customers who are likely to make the target action (for instance, install an app) only when treated (for instance, received a push).
+
+* Combine a churn model and an uplift model to offer some bonus to a group of customers who are likely to churn.
+
+* Select a tiny group of customers in the campaign where a price per customer is high.
 
 Read more about uplift modeling problem in `User Guide <https://scikit-uplift.readthedocs.io/en/latest/user_guide/index.html>`__,
-also articles in russian on habr.com: `Part 1 <https://habr.com/ru/company/ru_mts/blog/485980/>`__
+
+Articles in russian on habr.com: `Part 1 <https://habr.com/ru/company/ru_mts/blog/485980/>`__
 and `Part 2 <https://habr.com/ru/company/ru_mts/blog/485976/>`__.
 
 **Features**:
 
-* Comfortable and intuitive style of modelling like scikit-learn;
+* Сomfortable and intuitive scikit-learn-like API;
 
-* Applying any estimator adheres to scikit-learn conventions;
+* Applying any estimator compatible with scikit-learn (e.g. Xgboost, LightGBM, Catboost, etc.);
 
 * All approaches can be used in sklearn.pipeline (see example (`EN <https://nbviewer.jupyter.org/github/maks-sh/scikit-uplift/blob/master/notebooks/pipeline_usage_EN.ipynb>`__ |Open In Colab3|_, `RU <https://nbviewer.jupyter.org/github/maks-sh/scikit-uplift/blob/master/notebooks/pipeline_usage_RU.ipynb>`__ |Open In Colab4|_));
 
-* Almost all implemented approaches solve both the problem of classification and regression;
+* Almost all implemented approaches solve classification and regression problem;
 
-* A lot of metrics (Such as *Area Under Uplift Curve* or *Area Under Qini Curve*) are implemented to evaluate your uplift model;
+* More uplift metrics that you have ever seen in one place! Include brilliants like  *Area Under Uplift Curve* (AUUC) or *Area Under Qini Curve* (Qini coefficient) with ideal cases;
 
-* Useful graphs for analyzing the built model.
+* Nice and useful viz for analyzing a performance model.
 
 Installation
 -------------
@@ -149,7 +158,7 @@ See the **RetailHero tutorial notebook** (`EN <https://nbviewer.jupyter.org/gith
     # import vizualisation tools
     from sklift.viz import plot_qini_curve
 
-    plot_qini_curve(y_true=y_val, uplift=uplift_preds, treatment=treat_val)
+    plot_qini_curve(y_true=y_val, uplift=uplift_preds, treatment=treat_val, negative_effect=True)
 
 .. image:: docs/_static/images/Readme_qini_curve.png
     :width: 514px
@@ -164,6 +173,8 @@ We welcome new contributors of all experience levels.
 - Please see our `Contributing Guide <https://scikit-uplift.readthedocs.io/en/latest/contributing.html>`_ for more details.
 - By participating in this project, you agree to abide by its `Code of Conduct <https://github.com/maks-sh/scikit-uplift/blob/master/.github/CODE_OF_CONDUCT.md>`__.
 
+If you have any questions, please contact us at team@uplift-modeling.com
+
 Contributing
 ~~~~~~~~~~~~~~~
 

docs/Readme.rst

@@ -1,9 +1,9 @@
-.. _scikit-uplift.readthedocs.io: https://scikit-uplift.readthedocs.io/en/latest/
+.. _uplift-modeling.com: https://www.uplift-modeling.com/en/latest/index.html
 
 Documentation
 ===============
 
-The full documentation is available at `scikit-uplift.readthedocs.io`_.
+The full documentation is available at `uplift-modeling.com`_.
 
 Or you can build the documentation locally using `Sphinx <http://sphinx-doc.org/>`_ 1.4 or later:
 

docs/api/datasets/clear_data_dir.rst

@@ -0,0 +1,5 @@
+*****************************************
+`sklift.datasets <./>`_.clear_data_dir
+*****************************************
+
+.. autofunction:: sklift.datasets.datasets.clear_data_dir

docs/api/datasets/fetch_criteo.rst

@@ -0,0 +1,9 @@
+.. _Criteo:
+
+**************************************
+`sklift.datasets <./>`_.fetch_criteo
+**************************************
+
+.. autofunction:: sklift.datasets.datasets.fetch_criteo
+
+.. include:: ../../../sklift/datasets/descr/criteo.rst

docs/api/datasets/fetch_hillstrom.rst

@@ -0,0 +1,9 @@
+.. _Hillstrom:
+
+****************************************
+`sklift.datasets <./>`_.fetch_hillstrom
+****************************************
+
+.. autofunction:: sklift.datasets.datasets.fetch_hillstrom
+
+.. include:: ../../../sklift/datasets/descr/hillstrom.rst

docs/api/datasets/fetch_lenta.rst

@@ -0,0 +1,9 @@
+.. _Lenta:
+
+***********************************
+`sklift.datasets <./>`_.fetch_lenta
+***********************************
+
+.. autofunction:: sklift.datasets.datasets.fetch_lenta
+
+.. include:: ../../../sklift/datasets/descr/lenta.rst

docs/api/datasets/fetch_x5.rst

@@ -0,0 +1,9 @@
+.. _X5:
+
+***********************************
+`sklift.datasets <./>`_.fetch_x5
+***********************************
+
+.. autofunction:: sklift.datasets.datasets.fetch_x5
+
+.. include:: ../../../sklift/datasets/descr/x5.rst

docs/api/datasets/get_data_dir.rst

@@ -0,0 +1,5 @@
+*****************************************
+`sklift.datasets <./>`_.get_data_dir
+*****************************************
+
+.. autofunction:: sklift.datasets.datasets.get_data_dir

docs/api/datasets/index.rst

@@ -0,0 +1,13 @@
+************************
+`sklift <../>`_.datasets
+************************
+
+.. toctree::
+   :maxdepth: 3
+
+   ./clear_data_dir
+   ./get_data_dir
+   ./fetch_lenta
+   ./fetch_x5
+   ./fetch_criteo
+   ./fetch_hillstrom

docs/api/index.rst

@@ -15,3 +15,4 @@ This is the modules reference of scikit-uplift.
    ./models/index
    ./metrics/index
    ./viz/index
+   ./datasets/index