Get Started
This website contains the documentation for the package bornrule
available on PyPI.
The package implements the classifier proposed in the paper:
Emanuele Guidotti and Alfio Ferrara. Text Classification with Born’s Rule. Advances in Neural Information Processing Systems, 2022.
Installation
Usage
Scikit-Learn
- Use it as any other
sklearn
classifier - Supports both dense and sparse input and GPU-accelerated computing via
cupy
- Documentation available here
PyTorch
- Use it as any other
torch
layer - Supports real and complex-valued inputs. Outputs probabilities in the range [0, 1]
- Documentation available here
SQL
- Use it for in-database classification
- Supports inputs represented as json
{feature: value, ...}
- Documentation available here
Cite as
@inproceedings{guidotti2022text,
title={Text Classification with Born's Rule},
author={Emanuele Guidotti and Alfio Ferrara},
booktitle={Advances in Neural Information Processing Systems},
editor={Alice H. Oh and Alekh Agarwal and Danielle Belgrave and Kyunghyun Cho},
year={2022},
url={https://openreview.net/forum?id=sNcn-E3uPHA}
}