Classification with Born's rule
Project description
This package implements the classifier proposed in:
Emanuele Guidotti and Alfio Ferrara. Text Classification with Born’s Rule. Advances in Neural Information Processing Systems, 2022.
Usage
Scikit-Learn
from bornrule import BornClassifier
- Use it as any other
sklearn
classifier - Supports both dense and sparse input and GPU-accelerated computing via
cupy
- Documentation available here
PyTorch
from bornrule.torch import Born
- Use it as any other
torch
layer - Supports real and complex-valued inputs. Outputs probabilities in the range [0, 1]
- Documentation available here
SQL
from bornrule.sql import BornClassifierSQL
- Use it for in-database classification
- Supports inputs represented as json
{feature: value, ...}
- Documentation available here
Paper replication
The replication code is available at https://github.com/eguidotti/bornrule
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}
}
Project details
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