pdi-Bagging: A Proposal of Bagging-Type Ensemble Method Generating Virtual Data

Honoka Irie, Isao Hayashi

2023

Abstract

For pattern classification problems, there is ensemble learning method that identifies multiple weak classifiers by the learning data and combines them together to improve the discrimination rate of testing data. We have already proposed pdi-Bagging (Possibilistic Data Interpolation-Bagging) which improves the discrimination rate of testing data by adding virtually generated data to learning data. In this paper, we propose a new method to specify the generation area of virtual data and change the generation class of virtual data. As a result, the discriminant accuracy is improved since five new bagging methods which generate virtual data around correct discrimination data and error discrimination data are formulated, and the class of virtual data is determined with the proposed new evaluation index in multidimensional space. We formulate a new pdi-Bagging algorithm, and discuss the usefulness of the proposed method using numerical examples.

Paper Citation

in Harvard Style

Irie H. and Hayashi I. (2023). pdi-Bagging: A Proposal of Bagging-Type Ensemble Method Generating Virtual Data. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, ISBN 978-989-758-623-1, pages 956-963. DOI: 10.5220/0011827600003393

in Bibtex Style

@conference{icaart23,
author={Honoka Irie and Isao Hayashi},
title={pdi-Bagging: A Proposal of Bagging-Type Ensemble Method Generating Virtual Data},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,},
year={2023},
pages={956-963},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011827600003393},
isbn={978-989-758-623-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,
TI - pdi-Bagging: A Proposal of Bagging-Type Ensemble Method Generating Virtual Data
SN - 978-989-758-623-1
AU - Irie H.
AU - Hayashi I.
PY - 2023
SP - 956
EP - 963
DO - 10.5220/0011827600003393