anh05 / nguyendsaa2021

Repository corresponding to the comparison of hyperparameter optimization approaches for class imbalance

Introduction

This folder contains all necessary scripts, figures, data for the paper Improved Automated CASH Optimization with Tree Parzen Estimators for Class Imbalance Problems.

Requiremnts

For this project to run you need:

• Python 3.6.0
• Scikit-learn 0.23.2
• Imbalanced-learn 0.7.0
• Hyperopt 0.2.5

Citation

Paper Reference

Duc Anh Nguyen, Jiawen Kong, Hao Wang, Stefan Menzel, Bernhard Sendhoff, Anna V. Kononova and Thomas Bäck. Improved Automated CASH Optimization with Tree Parzen Estimators for Class Imbalance Problems. The 8th IEEE International Conference on Data Science and Advanced Analytics (DSAA2021).

BibTex Reference

@INPROCEEDINGS{9564147,
author={Nguyen, Duc Anh and Kong, Jiawen and Wang, Hao and Menzel, Stefan and Sendhoff, Bernhard and Kononova, Anna V. and Bäck, Thomas},
booktitle={2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA)},
title={Improved Automated CASH Optimization with Tree Parzen Estimators for Class Imbalance Problems},
year={2021},
pages={1-9},
doi={10.1109/DSAA53316.2021.9564147}}

Contact us

Duc Anh Nguyen

Email:d-dot-a-dot-nguyen-at-liacs-dot-leidenuniv-dot-nl

Acknowledgement

• This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement number 766186 (ECOLE).