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

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Metadata Harvesting (OAI2)
  • Digital Archiving Policy
  • Promote your Publication

IJACSA

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

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors

Future of Information and Communication Conference (FICC)

  • 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
  • Guidelines
  • Fees
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Subscribe

Article Details

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.

Improvement on Classification Models of Multiple Classes through Effectual Processes

Author 1: Tarik A. Rashid

Download PDF

Digital Object Identifier (DOI) : 10.14569/IJACSA.2015.060709

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 6 Issue 7, 2015.

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

Abstract: Classify cases in one of two classes referred to as a binary classification. However, some classification algorithms will allow, of course the use of more than two classes. This research work focuses on improving the results of classification models of multiple classes via some effective techniques. A case study of students’ achievement at Salahadin University is used in this research work. The collected data are pre-processed, cleaned, filtered, normalised, the final data was balanced and randomised, then a combining technique of Naïve Base Classifier and Best First Search algorithms are used to ultimately reduce the number of features in data sets. Finally, a multi-classification task is conducted through some effective classifiers such as K-Nearest Neighbor, Radial Basis Function, and Artificial Neural Network to forecast the students’ performance.

Keywords: Non-Balanced Data; Feature Selection; Multiple Classification; Machine Learning Techniques; Student Performance Forecasting

Tarik A. Rashid, “Improvement on Classification Models of Multiple Classes through Effectual Processes” International Journal of Advanced Computer Science and Applications(IJACSA), 6(7), 2015. http://dx.doi.org/10.14569/IJACSA.2015.060709

@article{Rashid2015,
title = {Improvement on Classification Models of Multiple Classes through Effectual Processes},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2015.060709},
url = {http://dx.doi.org/10.14569/IJACSA.2015.060709},
year = {2015},
publisher = {The Science and Information Organization},
volume = {6},
number = {7},
author = {Tarik A. Rashid}
}


IJACSA

Upcoming Conferences

Future of Information and Communication Conference (FICC) 2023

2-3 March 2023

  • Virtual

Computing Conference 2023

22-23 June 2023

  • London, United Kingdom

IntelliSys 2023

7-8 September 2023

  • Amsterdam, The Netherlands

Future Technologies Conference (FTC) 2023

2-3 November 2023

  • San Francisco, United States
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

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

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

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

© The Science and Information (SAI) Organization Limited. Registered in England and Wales. Company Number 8933205. All rights reserved. thesai.org