On the Performance Assessment and Comparison of Features Selection Approaches

Authors

  • Seyyid Ahmed Medjahed University of Relizane
  • Fatima Boukhatem Djillali Liabes University, Sidi Bel Abbes, Algeria

DOI:

https://doi.org/10.13053/cys-28-2-4211

Keywords:

Feature selection, Classification, Stability, Support Vector Machine

Abstract

In many supervised learning problems, feature selection techniques have become an apparent need in many applications. Feature selection significantly influences the classification accuracy rate and the quality of SVM model by reducing the number of feature, remove irrelevant and redundant features. In this paper, we evaluate the performance of twenty feature selection algorithms over four databases. The performance is conducted in term of: classification accuracy rate, Kuncheva’s Stability, Information Stability, SS Stability and SH Stability. To measure the feature selection algorithms, several datasets in UCI machine learning repository are adopted to calculate the classification accuracy rate and the different stability.

Downloads

Additional Files

Published

2024-06-12

Issue

Vol. 28 No. 2 (2024): 28(2) 2024

Section

Articles

License 

Hereby I transfer exclusively to the Journal "Computación y 
Sistemas", published by the Computing Research Center (CIC-IPN),
the Copyright of the aforementioned paper. I also accept that these 
rights will not be transferred to any other publication, in any other 
format, language or other existing means of developing.
I certify that the paper has not been previously disclosed or simultaneo
usly submitted to any other publication, and that it does not contain 
material whose publication would violate the Copyright or other 
proprietary rights of any person, company or institution. I certify that 
I have the permission from the institution or company where I work or 
study to publish this work.
The representative author accepts the responsibility for the publication
of this paper on behalf of each and every one of the authors. 
This transfer is subject to the following conditions:
  • The authors retain all ownership rights (such as patent rights) of this work, except for the publishing rights transferred to the CIC, through this document.
  • Authors retain the right to publish the work in whole or in part in any book they are the authors or publishers. They can also make use of this work in conferences, courses, personal web pages, and so on.
  • Authors may include working as part of his thesis, for non-profit distribution only.