Improving SVM Classification on Imbalanced Datasets for EEG-Based Person Authentication

Nga Tran, Dat Tran, Shuangzhe Liu, Linh Trinh, Tien Pham

Research output: A Conference proceeding or a Chapter in BookConference contribution

1 Citation (Scopus)

Abstract

Support Vector Machine (SVM) has been widely used in EEG-based person authentication. Current EEG datasets are often imbalanced due to the frequency of genuine clients and impostors, and this issue heavily impacts on the performance of EEG-based person authentication using SVM. In this paper, we propose a new bias method for SVM binary classification to improve the performance of the minority class in imbalanced datasets. Our experiments on EEG datasets and UCI datasets with the proposed method show promising results.

Original languageEnglish
Title of host publicationInternational Joint Conference: 12th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2019) and 10th International Conference on EUropean Transnational Education (ICEUTE 2019). CISIS 2019, ICEUTE 2019
EditorsJosé António Sáez Muñoz, Emilio Corchado, Francisco Martínez Álvarez, Alicia Troncoso Lora, Héctor Quintián
Place of PublicationSwitzerland
PublisherSpringer
Pages57-66
Number of pages10
ISBN (Electronic)9783030200053
ISBN (Print)9783030200046
DOIs
Publication statusPublished - 1 Jan 2020
EventInternational Joint Conference: 12th International Conference on Computational Intelligence in Security for Information Systems, CISIS 2019 and 10th International Conference on European Transnational Education, ICEUTE 2019 - Seville, Spain
Duration: 13 May 201915 May 2019

Publication series

NameAdvances in Intelligent Systems and Computing
Volume951
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

ConferenceInternational Joint Conference: 12th International Conference on Computational Intelligence in Security for Information Systems, CISIS 2019 and 10th International Conference on European Transnational Education, ICEUTE 2019
CountrySpain
CitySeville
Period13/05/1915/05/19

Fingerprint Dive into the research topics of 'Improving SVM Classification on Imbalanced Datasets for EEG-Based Person Authentication'. Together they form a unique fingerprint.

  • Cite this

    Tran, N., Tran, D., Liu, S., Trinh, L., & Pham, T. (2020). Improving SVM Classification on Imbalanced Datasets for EEG-Based Person Authentication. In J. A. Sáez Muñoz, E. Corchado, F. Martínez Álvarez, A. Troncoso Lora, & H. Quintián (Eds.), International Joint Conference: 12th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2019) and 10th International Conference on EUropean Transnational Education (ICEUTE 2019). CISIS 2019, ICEUTE 2019 (pp. 57-66). (Advances in Intelligent Systems and Computing; Vol. 951). Springer. https://doi.org/10.1007/978-3-030-20005-3_6