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}
}
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
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