Support Vector Machine Performance Improvements by Using Sine Cosine Algorithm
- Title
- Support Vector Machine Performance Improvements by Using Sine Cosine Algorithm
- Creator
- Zivkovic M.; Vukobrat N.; Chhabra A.; Rashid T.A.; Venkatachalam K.; Bacanin N.
- Description
- The optimization of parameters has a crucial influence on the solution efficacy and the accuracy of the support vector machine (SVM) in the machine learning domain. Some of the typical approaches for determining the parameters of the SVM consider the grid search approach (GS) and some of the representative swarm intelligence metaheuristics. On the other side, most of those SVM implementations take into the consideration only the margin, while ignoring the radius. In this paper, a novel radiusmargin SVM approach is implemented that incorporates the enhanced sine cosine algorithm (eSCA). The proposed eSCA-SVM method takes into the account both maximizing the margin and minimizing the radius. The eSCA has been used to optimize the penalty and RBF parameter in SVM. The proposed eSCA-SVM method has been evaluated against four binary UCI datasets and compared to seven other algorithms. The experimental results suggest that the proposed eSCA-SVM approach has superior performances in terms of the average classification accuracy than other methods included in the comparative analysis. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
- Source
- Lecture Notes on Data Engineering and Communications Technologies, Vol-114, pp. 791-803.
- Date
- 2022-01-01
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Subject
- Machine learning; Parameter optimization; Radiusmargin error; Sine cosine algorithm; Support vector machine (SVM)
- Coverage
- Zivkovic M., Singidunum University, Danijelova 32, Belgrade, 11000, Serbia; Vukobrat N., Singidunum University, Danijelova 32, Belgrade, 11000, Serbia; Chhabra A., Guru Nanak Dev University, Amritsar, India; Rashid T.A., Computer Science and Engineering Department, University of Kurdistan Hewler, KRG, Erbil, Iraq; Venkatachalam K., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, India; Bacanin N., Singidunum University, Danijelova 32, Belgrade, 11000, Serbia
- Rights
- Restricted Access
- Relation
- ISSN: 23674512
- Format
- Online
- Language
- English
- Type
- Book chapter
Collection
Citation
Zivkovic M.; Vukobrat N.; Chhabra A.; Rashid T.A.; Venkatachalam K.; Bacanin N., “Support Vector Machine Performance Improvements by Using Sine Cosine Algorithm,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 23, 2025, https://archives.christuniversity.in/items/show/18653.