2-Dimensional homogeneous distributed ensemble feature selection

Machmud R. Alhamidi, Dewa M.S. Arsa, Muhammad Febrian Rachmadi, Wisnu Jatmiko

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Abstract

A bstract—Big data can be seen from the number of its samples and features. The selection of the most representative feature is an important task in big data analysis to reduce the dimension. The feature selection method is used to handle this problem. In this research, a homogeneous distributed ensemble feature selection method with 2-dimensional partition is used as new approach of feature selection. The results showed that the proposed method can improve the accuracy from the other feature selection method with an increase of 2% for several datasets. In addition, it also speeds up the computation to almost two times faster.

Original languageEnglish
Title of host publication2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages367-372
Number of pages6
ISBN (Electronic)9781728101354
DOIs
Publication statusPublished - 17 Jan 2019
Event10th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018 - Yogyakarta, Indonesia
Duration: 27 Oct 201828 Oct 2018

Publication series

Name2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018

Conference

Conference10th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018
CountryIndonesia
CityYogyakarta
Period27/10/1828/10/18

Fingerprint

Feature extraction
data analysis

Keywords

  • 2D Ensem ble
  • Big data
  • Distributed
  • Feature selection
  • Hom ogeneous

Cite this

Alhamidi, M. R., Arsa, D. M. S., Rachmadi, M. F., & Jatmiko, W. (2019). 2-Dimensional homogeneous distributed ensemble feature selection. In 2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018 (pp. 367-372). [8618266] (2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICACSIS.2018.8618266
Alhamidi, Machmud R. ; Arsa, Dewa M.S. ; Rachmadi, Muhammad Febrian ; Jatmiko, Wisnu. / 2-Dimensional homogeneous distributed ensemble feature selection. 2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 367-372 (2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018).
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Alhamidi, MR, Arsa, DMS, Rachmadi, MF & Jatmiko, W 2019, 2-Dimensional homogeneous distributed ensemble feature selection. in 2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018., 8618266, 2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018, Institute of Electrical and Electronics Engineers Inc., pp. 367-372, 10th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018, Yogyakarta, Indonesia, 27/10/18. https://doi.org/10.1109/ICACSIS.2018.8618266

2-Dimensional homogeneous distributed ensemble feature selection. / Alhamidi, Machmud R.; Arsa, Dewa M.S.; Rachmadi, Muhammad Febrian; Jatmiko, Wisnu.

2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018. Institute of Electrical and Electronics Engineers Inc., 2019. p. 367-372 8618266 (2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018).

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

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Alhamidi MR, Arsa DMS, Rachmadi MF, Jatmiko W. 2-Dimensional homogeneous distributed ensemble feature selection. In 2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018. Institute of Electrical and Electronics Engineers Inc. 2019. p. 367-372. 8618266. (2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018). https://doi.org/10.1109/ICACSIS.2018.8618266