dzeiberg / bi-est

Estimating Bias in semi-supervised learning

bi-est

Estimating Bias in semi-supervised learning via Nested EM on Gaussian Mixture Models

Usage

The MATLAB directory contains the MATLAB code used in the orignal paper. main.m contains an optimization example for a dataset in dataset.mat for one initialization.

To run with your own data, specify data matrices unlabeled, labeled_pos, labeled_neg with samples as rows and featues as columns. Specify the number of components with num_componets and an optional progress bar.
Run optimization with

[alpha, negative_params, positive_params, w_labeled] = ...
    PNU_nested_em(unlabeled, labeled_pos, labeled_neg, num_components, ...
    progress_bar)

Reference

If you use this code for research, please cite our accompaying paper:

@inproceedings{depaoliskaluza2022bias,
  title={An Approach to Identifying and Quantifying Bias in Biomedical Data},
  author={De Paolis Kaluza, M. Clara and Jain, Shantanu and Radivojac, Predrag},
  booktitle={Pacific Symposium on Biocomputing 2023: Kohala Coast, Hawaii, USA, 3--7 January 2023},
  pages={311--322},
  year={2022},
}

License

This project is licensed under the MIT license found in the LICENSE file in this repository.