/EBDM

Implemented the research paper ‘A Unified Entropy-Based Distance Metric for Ordinal-and-Nominal-Attribute Data Clustering’ by Zhang et al. and built a python package for finding a common distance matrix for the ordinal and nominal data from any kind of questionnaire data, based on entropy measures. Tested the package on multiple datasets for robustness.

Primary LanguagePythonMIT LicenseMIT

EBDM

PyPI version

forthebadge made-with-python

Python package for finding Entropy-Based Distance Metric. An implementation of the following paper:

Y. Zhang, Y. Cheung and K. C. Tan, "A Unified Entropy-Based Distance Metric for Ordinal-and-Nominal-Attribute Data Clustering," in IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 1, pp. 39-52, Jan. 2020. doi: 10.1109/TNNLS.2019.2899381

Getting Started

Prerequisites

Note EBDM requires Python 3.x

These instructions will get you a copy of the package up and running on your local machine for development and testing purposes.

Before getting started, make sure that you have the following libraries already installed:

import pandas as pd
import math

Installing

pip install EBDM

Importing in your project

In your source file, import the library and start using the functions step-by-step as mentioned in the below section

import EBDM as ebd

For accessing modules, use

ebd.<module_name>

For reading the data, make sure that you’ve separated ordinal and nominal into separate CSV files.

Usage

nominal_features_dict = ebd.read_nom('nominal_data.csv')
ordinal_features_dict = ebd.read_ord('ordinal_data.csv')

Contributing

Feel free to make contributions to this repository by submitting well-documented pull requests and raising issues.

Documentation

To run the documentation website, open docs/_build/html/index.html

If you're making changes to the source code of docs folder, make sure that you compile a clean build in the shell using make clean; make html

Authors

License

This project is licensed under the MIT License - see the LICENSE.md file for details

Acknowledgments

  • Sincere thanks to Dr. Mitali Mukerjee, Dr. Bhavana Prasher, Mr. Rintu Kutum and the AyurGenomics Group for guiding us throughout our internship period at the CSIR-IGIB, New Delhi.