https://github.com/ustunb/risk-SLIM

simple customizable risk scores in python
https://github.com/ustunb/risk-SLIM

Last synced: 2 months ago
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simple customizable risk scores in python

• Host: GitHub
• URL: https://github.com/ustunb/risk-SLIM
• Owner: ustunb
• License: bsd-3-clause
• Created: 2017-02-20T04:19:12.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2023-06-30T23:29:58.000Z (12 months ago)
• Last Synced: 2024-01-25T16:05:02.078Z (5 months ago)
• Language: Python
• Homepage:
• Size: 14.9 MB
• Stars: 130
• Watchers: 9
• Forks: 33
• Open Issues: 8
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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• awesome-machine-learning-interpretability - Risk-SLIM - SLIM?style=social) | "a machine learning method to fit simple customized risk scores in python.” | (Technical Resources / Open Source/Access Responsible AI Software Packages)

README

        
risk-slim

========

risk-slim is a machine learning method to fit simple customized risk scores in python. 

#### Background 

Risk scores let users make quick risk predictions by adding and subtracting a few small numbers (see e.g., 500 + medical risk scores at [mdcalc.com](https://www.mdcalc.com/)). 

Here is a risk score for ICU risk prediction from our [paper](http://www.berkustun.com/docs/ustun_2017_optimized_risk_scores.pdf). 











#### Video



	

		

	



 


#### Reference

If you use risk-slim in your research, we would appreciate a citation to the following paper ([bibtex](/docs/references/ustun2019riskslim.bib)!

Learning Optimized Risk Scores 


Berk Ustun and Cynthia Rudin


Journal of Machine Learning Research, 2019.

## Installation

Run the following snippet in a Unix terminal to install risk-slim and complete a test run.  

```

git clone https://github.com/ustunb/risk-slim

cd risk-slim

pip install -e . 		# install in editable mode  

bash batch/job_template.sh 	# batch run

```

### Requirements

risk-slim requires Python 3.5+ and CPLEX 12.6+. For instructions on how to download and install, click [here](/docs/cplex_instructions.md). 

## Contributing

I'm planning to pick up development again in Fall 2020. I can definitely use a hand! If you are interested in contributing, please reach out!  

Here's the current development roadmap:

- [sci-kit learn interface](http://scikit-learn.org/stable/developers/contributing.html#rolling-your-own-estimator)

- support for open source solver in [python-mip](https://github.com/coin-or/python-mip)

- basic reporting tools (roc curves, calibration plots, model reports)

- documentation

- pip