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https://github.com/elo7/autoshap
AutoSHAP is a framework to automate explainable machine learning
https://github.com/elo7/autoshap
Last synced: about 2 months ago
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AutoSHAP is a framework to automate explainable machine learning
- Host: GitHub
- URL: https://github.com/elo7/autoshap
- Owner: elo7
- License: mit
- Created: 2020-02-10T14:11:51.000Z (almost 5 years ago)
- Default Branch: master
- Last Pushed: 2022-09-30T19:58:09.000Z (over 2 years ago)
- Last Synced: 2024-03-26T22:00:50.869Z (9 months ago)
- Language: Jupyter Notebook
- Size: 1.6 MB
- Stars: 0
- Watchers: 54
- Forks: 0
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# AutoSHAP
AutoSHAP is a library still in development by the [Elo7](https://www.elo7.com.br) data science and search teams.
AutoSHAP is a simple framework built on top of [SHAP](https://github.com/slundberg/shap) to make it simple to engineers access explanations in a daily basis setting just a few parameters. It has two main classes, _FullPipeline_ and _SHAPViews_. The first runs the entire pipeline depicted in image bellow, i.e., it instances a [XGBoost](https://xgboost.readthedocs.io/en/latest/) model, makes hyperparameter optimization, computes the Shapley values with the best model, saves the XGBoost model and data and make plots as a result.
The second class, _SHAPViews_, allows one to see interactive plots of features and Shapley values. This is specially useful to analyze the distribution of some feature values while filtering them by some chosen Shapley Values.
## Installation
Clone this repository,
```bash
git clone [email protected]:elo7/AutoSHAP.git
```
and inside it use pip to install:
```bash
pip install .
```
## Examples
You can check application examples in the [notebooks](notebooks/)