Categorical Locality

This repository contains the implementation source code of the following paper:

Interpreting Categorical Data Classifiers using Explanation-based Locality

BibTeX:

@inproceedings{rasouli2022interpreting,
              title={Interpreting Categorical Data Classifiers using Explanation-based Locality},
              author={Rasouli, Peyman and Yu, Ingrid Chieh and Jim{\'e}nez-Ruiz, Ernesto},
              booktitle={2022 IEEE International Conference on Data Mining Workshops (ICDMW)},
              pages={163--170},
              year={2022},
              organization={IEEE}
}

Setup

1- Clone the repository using HTTP/SSH:

git clone https://github.com/peymanrasouli/categorical_locality

2- Create a conda virtual environment:

conda create -n categorical_locality python=3.6

3- Activate the conda environment:

conda activate categorical_locality

4- Standing in categorical_locality directory, install the requirements:

pip install -r requirements.txt

Reproducing the results

To reproduce the explanation results of categorical_locality method vs. baselines with:

1- Linear Regression as interpretable model run:

python local_explanation_lr.py

2- Decision Tree as interpretable model run:

python local_explanation_dt.py