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https://github.com/racarvajal/eso_python_coffee_shap

Introduction to SHAP analysis of ML models
https://github.com/racarvajal/eso_python_coffee_shap

Last synced: 18 days ago
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Introduction to SHAP analysis of ML models

Host: GitHub
URL: https://github.com/racarvajal/eso_python_coffee_shap
Owner: racarvajal
License: mit
Created: 2024-05-17T23:46:31.000Z (8 months ago)
Default Branch: main
Last Pushed: 2024-06-19T14:44:36.000Z (7 months ago)
Last Synced: 2024-11-10T03:05:57.281Z (3 months ago)
Language: Jupyter Notebook
Size: 27.3 MB
Stars: 0
Watchers: 1
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

README

        # ESO_python_coffee_SHAP

[![My Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/racarvajal/ESO_python_coffee_SHAP/main?filepath=Intro_SHAP.ipynb) [![nbviewer](https://img.shields.io/badge/view%20in-nbviewer-orange)](https://nbviewer.org/github/racarvajal/ESO_python_coffee_SHAP/blob/main/Intro_SHAP.ipynb) 

  



Introduction to SHAP analysis of ML models

Short explanation of the use of SHAP analysis for the selection of relevant features in regular functions and Machine Learning (ML) models.

A first example with a toy function is shown. It is followed by an astrophysical example for the prediction of redshift values in QSOs in the SDSS-DR16Q sample. Finally, an astrophysics-based example with images is presented.