🔨 Fix minor improvements on docs (#153)

* 📗 Fix megafon title overline

* 📗 Rename EDA notebooks

* 📗 Rename EDA notebooks

* 💫 Add EDA in tutorials

* 💫 Add link from readme to tutorial page

* 💫 Fix warning of toctree for 404 page

* 📝 Fix typo in DESCR docstring

* 📝 Fix index of docs

* 📝 Fix main Readme

* 📝 Fix quick start

* 👷 Fix 404 page image

* 👷 Improve docstrings

* 👷 Improve legend name in display

* 👷 Fix bug in uplift display

* 👷 Update images

* 👷 Update quick start Readme

* 🔧 Update .gitignore: add  pytest.xml

* Remove old image

* Fix links in changelog

* 📦 Build only html

* ⬆️ Replace depricated recommonmark with myst

Author: maks-sh

.gitignore

@@ -62,6 +62,7 @@ coverage.xml
 *.cover
 .hypothesis/
 .pytest_cache/
+pytest.xml
 
 # Translations
 *.mo

.readthedocs.yml

@@ -13,7 +13,8 @@ sphinx:
 #  configuration: mkdocs.yml
 
 # Optionally build your docs in additional formats such as PDF and ePub
-formats: all
+formats:
+  - htmlzip
 
 # Optionally set the version of Python and requirements required to build your docs
 python:

Readme.rst

@@ -54,19 +54,22 @@ Articles in russian on habr.com: `Part 1 <https://habr.com/ru/company/ru_mts/blo
 `Part 2 <https://habr.com/ru/company/ru_mts/blog/485976/>`__
 and `Part 3 <https://habr.com/ru/company/ru_mts/blog/538934/>`__.
 
-**Features**:
+Why sklift
+-------------
+
+- Сomfortable and intuitive *scikit-learn*-like API;
 
-* Сomfortable and intuitive scikit-learn-like API;
+- More uplift metrics than 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;
 
-* Applying any estimator compatible with scikit-learn (e.g. Xgboost, LightGBM, Catboost, etc.);
+- Supporting 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|_));
+- All approaches can be used in the ``sklearn.pipeline``. See the example of usage on `the Tutorials page <https://www.uplift-modeling.com/en/latest/tutorials.html>`__;
 
-* Almost all implemented approaches solve classification and regression problem;
+- Also metrics are compatible with the classes from ``sklearn.model_selection``. See the example of usage on `the Tutorials page <https://www.uplift-modeling.com/en/latest/tutorials.html>`__;
 
-* 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;
+- Almost all implemented approaches solve classification and regression problems;
 
-* Nice and useful viz for analyzing a performance model.
+- Nice and useful viz for analysing a performance model.
 
 Installation
 -------------
@@ -112,24 +115,25 @@ Use the intuitive python API to train uplift models with `sklift.models  <https:
 .. code-block:: python
 
     # import approaches
-    from sklift.models import SoloModel, ClassTransformation, TwoModels
+    from sklift.models import SoloModel, ClassTransformation
     # import any estimator adheres to scikit-learn conventions.
-    from catboost import CatBoostClassifier
-
+    from lightgbm import LGBMClassifier
 
     # define models
-    treatment_model = CatBoostClassifier(iterations=50, thread_count=3,
-                                         random_state=42, silent=True)
-    control_model = CatBoostClassifier(iterations=50, thread_count=3,
-                                       random_state=42, silent=True)
+    estimator = LGBMClassifier(n_estimators=10)
+
+    # define metamodel
+    slearner = SoloModel(estimator=estimator)
 
-    # define approach
-    tm = TwoModels(treatment_model, control_model, method='vanilla')
     # fit model
-    tm = tm.fit(X_train, y_train, treat_train)
+    slearner.fit(
+        X=X_tr,
+        y=y_tr,
+        treatment=trmnt_tr,
+    )
 
     # predict uplift
-    uplift_preds = tm.predict(X_val)
+    uplift_slearner = slearner.predict(X_val)
 
 **Evaluate your uplift model**
 
@@ -144,33 +148,48 @@ Uplift model evaluation metrics are available in `sklift.metrics  <https://www.u
 
 
     # Uplift@30%
-    tm_uplift_at_k = uplift_at_k(y_true=y_val, uplift=uplift_preds, treatment=treat_val,
-                                 strategy='overall', k=0.3)
+    uplift_at_k = uplift_at_k(y_true=y_val, uplift=uplift_slearner,
+                              treatment=trmnt_val,
+                              strategy='overall', k=0.3)
 
     # Area Under Qini Curve
-    tm_qini_auc = qini_auc_score(y_true=y_val, uplift=uplift_preds, treatment=treat_val)
+    qini_coef = qini_auc_score(y_true=y_val, uplift=uplift_slearner,
+                               treatment=trmnt_val)
 
     # Area Under Uplift Curve
-    tm_uplift_auc = uplift_auc_score(y_true=y_val, uplift=uplift_preds, treatment=treat_val)
+    uplift_auc = uplift_auc_score(y_true=y_val, uplift=uplift_slearner,
+                                  treatment=trmnt_val)
 
     # Weighted average uplift
-    tm_wau = weighted_average_uplift(y_true=y_val, uplift=uplift_preds,  treatment=treat_val)
+    wau = weighted_average_uplift(y_true=y_val, uplift=uplift_slearner,
+                                  treatment=trmnt_val)
 
 **Vizualize the results**
 
 Visualize performance metrics with `sklift.viz  <https://www.uplift-modeling.com/en/latest/api/viz/index.html>`__.
 
 .. code-block:: python
 
-    # import vizualisation tools
     from sklift.viz import plot_qini_curve
+    import matplotlib.pyplot as plt
+
+    fig, ax = plt.subplots(1, 1)
+    ax.set_title('Qini curves')
+
+    plot_qini_curve(
+        y_test, uplift_slearner, trmnt_test,
+        perfect=True, name='Slearner', ax=ax
+    );
 
-    plot_qini_curve(y_true=y_val, uplift=uplift_preds, treatment=treat_val, negative_effect=True)
+    plot_qini_curve(
+        y_test, uplift_revert, trmnt_test,
+        perfect=False, name='Revert label', ax=ax
+    );
 
-.. image:: docs/_static/images/Readme_qini_curve.png
+.. image:: docs/_static/images/quick_start_qini.png
     :width: 514px
     :height: 400px
-    :alt: Example of model's qini curve, perfect qini curve and random qini curve
+    :alt: Example of some models qini curves, perfect qini curve and random qini curve
 
 Development
 -----------

docs/404.rst

@@ -1,8 +1,10 @@
+:orphan:
+
 *******************
 404 Page Not Found
 *******************
 
-.. image:: ../../_static/images/sklift_404.png
+.. image:: _static/images/sklift_404.png
    :alt: 404 Page not found
    :align: center
    :width: 250 px

docs/_static/images/Readme_qini_curve.png

@@ -1,8 +1,8 @@
 .. _Megafon:
 
-***********************************
+***************************************
 `sklift.datasets <./>`_.fetch_megafon
-***********************************
+***************************************
 
 .. autofunction:: sklift.datasets.datasets.fetch_megafon
 

docs/_static/images/quick_start_qini.png

@@ -10,17 +10,17 @@
 
 ## Version 0.3.2
 
-### [sklift.datasets](https://www.uplift-modeling.com/en/v0.3.1/api/datasets/index.html)
+### [sklift.datasets](https://www.uplift-modeling.com/en/v0.3.2/api/datasets/index.html)
 
-* 🔨 Fix bug in [fetch_x5](https://www.uplift-modeling.com/en/v0.3.1/api/datasets/fetch_x5.html) function by [@Muhamob](https://github.com/Muhamob).
+* 🔨 Fix bug in [fetch_x5](https://www.uplift-modeling.com/en/v0.3.2/api/datasets/fetch_x5.html) function by [@Muhamob](https://github.com/Muhamob).
 
-### [sklift.metrics](https://www.uplift-modeling.com/en/v0.3.1/api/index/metrics.html)
+### [sklift.metrics](https://www.uplift-modeling.com/en/v0.3.2/api/index/metrics.html)
 
-* 📝 Fix docstring in [uplift_by_percentile](https://www.uplift-modeling.com/en/v0.3.1/api/metrics/uplift_by_percentile.html) function by [@ElisovaIra](https://github.com/ElisovaIra).
+* 📝 Fix docstring in [uplift_by_percentile](https://www.uplift-modeling.com/en/v0.3.2/api/metrics/uplift_by_percentile.html) function by [@ElisovaIra](https://github.com/ElisovaIra).
 
-### [sklift.viz](https://www.uplift-modeling.com/en/v0.3.1/api/viz/index.html)
+### [sklift.viz](https://www.uplift-modeling.com/en/v0.3.2/api/viz/index.html)
 
-* 🔨 Fix bug in [plot_uplift_preds](https://www.uplift-modeling.com/en/v0.3.1/api/viz/plot_uplift_preds.html) function by [@bwbelljr](https://github.com/bwbelljr).
+* 🔨 Fix bug in [plot_uplift_preds](https://www.uplift-modeling.com/en/v0.3.2/api/viz/plot_uplift_preds.html) function by [@bwbelljr](https://github.com/bwbelljr).
 
 ### Miscellaneous