Develop (#28)

* Add documents (#27)

* Adding methods and checks.

* More rigorous check for evaluator's shape
* add ``concat`` method for ``UserTrainTestInteractionPair``

* Fix bug.

* Improved documents and examples

* Workflow modification

.github/workflows/wheels.yml

@@ -3,7 +3,6 @@ on:
   push:
     branches:
       - main
-      - develop
   release:
     types:
       - created
@@ -70,7 +69,7 @@ jobs:
           verbose: true
           skip_existing: true
       - name: Publish package to PyPI
-        if: github.event_name == 'push' && startsWith(github.ref, 'refs/tags')
+        if: github.event_name == 'release'
         uses: pypa/gh-action-pypi-publish@master
         with:
           user: __token__

Readme.md

@@ -7,7 +7,9 @@
 [![Read the Docs](https://readthedocs.org/projects/irspack/badge/?version=stable)](https://irspack.readthedocs.io/en/stable/)
 [![codecov](https://codecov.io/gh/tohtsky/irspack/branch/main/graph/badge.svg?token=kLgOKTQqcV)](https://codecov.io/gh/tohtsky/irspack)
 
-**irspack** is a Python package for train, evaluate, and optimize recommender systems based on implicit feedback.
+[**Docs**](https://irspack.readthedocs.io/en/latest/)
+
+**irspack** is a Python package to train, evaluate, and optimize recommender systems based on implicit feedback.
 
 There are already great packages for this purpose like
 

examples/evaluate-recommender.ipynb

@@ -61,7 +61,7 @@
    "source": [
     "## Split scheme 1. Hold-out for all users.\n",
     "\n",
-    "To cross-validate a recommender system trained with implicit feedback, the standard method is to hide some subset of the known user-item interactions as a validation set and see how the recommender ranks these hidden groundtruths:\n",
+    "To evaluate the performance of a recommender system trained with implicit feedback, the standard method is to hide some subset of the known user-item interactions as a validation set and see how the recommender ranks these hidden groundtruths:\n",
     "\n",
     "![Perform hold out for all users.](./split1.png \"split1\")\n",
     "\n",
@@ -265,7 +265,7 @@
    "source": [
     "So we see that `P3alphaRecommender` actually exhibits better accuracy scores compared to rather trivial `TopPopRecommender`.\n",
     "\n",
-    "In the next tutorial, we will optimize the recommender's performance using cross-validation."
+    "In the next tutorial, we will optimize the recommender's performance using the hold-out method."
    ]
   }
  ],