Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/ustunb/risk-slim
simple customizable risk scores in python
https://github.com/ustunb/risk-slim
Last synced: 3 months ago
JSON representation
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 (over 1 year ago)
- Last Synced: 2024-04-18T18:01:21.457Z (7 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
Awesome Lists containing this project
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