Analysis of Feature Selection Method for 3D Molecular Structure of Amphetamine-Type Stimulants (ATS) Drugs

Phoebe Ellyin Knight, Azah Kamilah Muda, Satrya Fajri Pratama

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes an improved method to analyze the effectiveness of ATS drugs identification by using a few feature selection methods such as Sequential Forward Floating Selection (SFFS), Sequential Forward Selection (SFS), Sequential Backward Floating Selection (SBFS), Sequential Backward Selection (SBS) and Support Vector Machine-Recursive Feature Elimination (SVM-RFE). The fundamental target of this paper is to compare which feature selection methods have better classification accuracy performance in identification for a large dataset. A comprehensive verification using WEKA is carried out to determine the performance of classification accuracy. This is achieved by comparing several classifiers with all features (without feature selection methods) and with selected features (with feature selection methods). From the experimental work, it was found that the performance of classification accuracy with selected features has similar accuracy if the performance accuracy done with all features. This shows that feature selection methods help to fasten and get better accuracy performance. The result also indicates that SFFS are the best feature selection methods to use to embed with SVM-RFE, while J48, IBk and Random Forest (RF) are the best three classifiers to use for future evaluation.

Original languageEnglish
Title of host publicationProceedings of the 13th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2021)
EditorsAjith Abraham, Andries Engelbrecht, Fabio Scotti, Niketa Gandhi, Pooja Manghirmalani Mishra, Giancarlo Fortino, Virgilijus Sakalauskas, Sabri Pllana
PublisherSpringer Science and Business Media Deutschland GmbH
Pages118-135
Number of pages18
ISBN (Print)9783030963019
DOIs
Publication statusPublished - 2022
Event13th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2021 and 13th World Congress on Nature and Biologically Inspired Computing, NaBIC 2021 - Virtual, Online
Duration: 15 Dec 202117 Dec 2021

Publication series

NameLecture Notes in Networks and Systems
Volume417 LNNS
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

Conference13th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2021 and 13th World Congress on Nature and Biologically Inspired Computing, NaBIC 2021
CityVirtual, Online
Period15/12/2117/12/21

Keywords

  • 3D molecular structure
  • Amphetamine-Type Stimulants (ATS)
  • As Sequential Forward Floating Selection (SFFS)
  • Drug image recognition
  • Feature selection method

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