Metadata-Version: 2.1
Name: expybox
Version: 0.0.5
Summary: Jupyter notebook toolbox for model interpretability/explainability
Home-page: https://github.com/Kukuksumusu/expybox
Author: Jakub Štercl
Author-email: stercjak@fit.cvut.cz
License: MIT
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.7
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: shap
Requires-Dist: pdpbox
Requires-Dist: lime
Requires-Dist: alibi
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: ipywidgets

[![Documentation Status](https://readthedocs.org/projects/expybox/badge/?version=latest)](https://expybox.readthedocs.io/en/latest/?badge=latest)

# ExpyBox
ExpyBox is a Jupyter notebook toolbox for model interpretability/explainability.
It lets you create interactive Jupyter notebooks to explain your model.

## Usage
This package is meant to be used inside of Jupyter notebook, other usage makes little to no sense.
First you need to import and instantiate the ExpyBox class:

```python
from expybox import ExpyBox
expybox = ExpyBox(predict_function, train_data, kernel_globals=globals())
```

Now you can use the supported interpretability methods, like this:
```python
expybox.lime()
```
which creates a form like this:


## Instalation
Because of *alibi* package ExpyBox requires **64-bit** Python 3.7 or higher. 
It is also recommended to create separate virtual enviroment - you can use Pythons 
[venv](https://docs.python.org/3/library/venv.html).

Otherwise the installation process is the same as for other packages, just use pip:
```bash
pip install expybox
``` 




