The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Outstanding Reviewers

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • ICONS_BA 2025

Computer Vision Conference (CVC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Editorial Board
  • Guidelines
  • Submit
  • Current Issue
  • Archives
  • Indexing
  • Fees
  • Reviewers
  • RSS Feed

DOI: 10.14569/IJACSA.2022.0131007
PDF

Application of Stacking Ensemble Machine in Big Data: Analyze the Determinants for Vitalization of the Multicultural Support Center

Author 1: Raeho Lee
Author 2: Haewon Byeon

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 10, 2022.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: For multicultural families to successfully promote social adaptation and achieve desirable social integration, the role of the multicultural family support center (Multi-FSC) is crucial. In addition, it's important to examine the factors that will contribute to the multicultural support center's vitality from the standpoint of the customers. In this study, machine learning models based on a single machine learning model and stacking ensemble using survey data from all multicultural families were used to examine the determinants for the utilization of multicultural family support centers for multicultural families. Additionally, based on the constructed prediction model, this study offered the foundational data for the revitalization of the multicultural support center. In this study, 281,606 adults (19 years or older), 56,273 of whom were married immigrants or naturalized citizens as of 2012, were examined. The stacking ensemble method was employed in this work to forecast the use of multicultural family support centers. In the base stage (model) of this model, logistic regression was employed, along with Classification and Regression Tree (CART), Radial Basis Function Neural Network (RBF-NN), and Random Forest (RF) model. The RBF-NN-Logit reg model had the best prediction performance, according to the study's findings (RMSE = 0.20, Ev = 0.45, and IA = 0.68). The findings of this study suggested that the prediction performance of the stacking ensemble can be improved when creating classification or prediction models using epidemiological data from a community.

Keywords: Stacking ensemble machine; radial basis function neural network; random forest; multicultural family support centers; prediction model

Raeho Lee and Haewon Byeon. “Application of Stacking Ensemble Machine in Big Data: Analyze the Determinants for Vitalization of the Multicultural Support Center”. International Journal of Advanced Computer Science and Applications (IJACSA) 13.10 (2022). http://dx.doi.org/10.14569/IJACSA.2022.0131007

@article{Lee2022,
title = {Application of Stacking Ensemble Machine in Big Data: Analyze the Determinants for Vitalization of the Multicultural Support Center},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0131007},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0131007},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {10},
author = {Raeho Lee and Haewon Byeon}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

Computer Vision Conference (CVC) 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

Artificial Intelligence Conference 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Future Technologies Conference (FTC) 2026

15-16 October 2026

  • Berlin, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computer Vision Conference
  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

The Science and Information (SAI) Organization Limited is a company registered in England and Wales under Company Number 8933205.