Supervised and Unsupervised Machine Learning Algorithms: An Empirical Evaluation

Rajarajan Rajkumar; Li Zhang; Vivian Sedov; Kamlesh Mistry

doi:10.1142/9789811294631_0038

Supervised and Unsupervised Machine Learning Algorithms: An Empirical Evaluation

Rajarajan Rajkumar, Li Zhang, Vivian Sedov, Kamlesh Mistry

Computer and Information Sciences Department

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Machine Learning (ML) algorithms are a subset of artificial intelligence that are applied to data with a primary focus of improving its accuracy over time by replicating and imitating the learning styles of human beings. Within this framework, several supervised and unsupervised learning algorithms are studied through different scenarios. The advantages and disadvantages of these algorithms are analysed through these case studies.

Original language	English
Title of host publication	Intelligent Management of Data and Information in Decision Making
Editors	Etienne E Kerre, Luis Martínez, Tianrui Li, Javier Montero , Pablo Flores-Vidal
Place of Publication	Singapore
Publisher	World Scientific
Pages	299-306
Number of pages	8
ISBN (Electronic)	9789811294631, 9789811294648
ISBN (Print)	9789811294624
DOIs	https://doi.org/10.1142/9789811294631_0038
Publication status	Published - 1 Aug 2024

Publication series

Name	World Scientific Proceedings Series on Computer Engineering and Information Science
Publisher	World Scientific
Volume	14
ISSN (Print)	1793-7868
ISSN (Electronic)	2972-4465

Keywords

Supervised and unsupervised learning algorithms
classification
clustering

Access to Document

10.1142/9789811294631_0038

Cite this

Rajkumar, R., Zhang, L., Sedov, V., & Mistry, K. (2024). Supervised and Unsupervised Machine Learning Algorithms: An Empirical Evaluation. In E. E. Kerre, L. Martínez, T. Li, J. Montero , & P. Flores-Vidal (Eds.), Intelligent Management of Data and Information in Decision Making (pp. 299-306). (World Scientific Proceedings Series on Computer Engineering and Information Science; Vol. 14). World Scientific. https://doi.org/10.1142/9789811294631_0038

Rajkumar, Rajarajan ; Zhang, Li ; Sedov, Vivian et al. / Supervised and Unsupervised Machine Learning Algorithms: An Empirical Evaluation. Intelligent Management of Data and Information in Decision Making. editor / Etienne E Kerre ; Luis Martínez ; Tianrui Li ; Javier Montero ; Pablo Flores-Vidal. Singapore : World Scientific, 2024. pp. 299-306 (World Scientific Proceedings Series on Computer Engineering and Information Science).

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Rajkumar, R, Zhang, L, Sedov, V & Mistry, K 2024, Supervised and Unsupervised Machine Learning Algorithms: An Empirical Evaluation. in EE Kerre, L Martínez, T Li, J Montero & P Flores-Vidal (eds), Intelligent Management of Data and Information in Decision Making. World Scientific Proceedings Series on Computer Engineering and Information Science, vol. 14, World Scientific, Singapore, pp. 299-306. https://doi.org/10.1142/9789811294631_0038

Supervised and Unsupervised Machine Learning Algorithms: An Empirical Evaluation. / Rajkumar, Rajarajan; Zhang, Li; Sedov, Vivian et al.
Intelligent Management of Data and Information in Decision Making. ed. / Etienne E Kerre; Luis Martínez; Tianrui Li; Javier Montero ; Pablo Flores-Vidal. Singapore: World Scientific, 2024. p. 299-306 (World Scientific Proceedings Series on Computer Engineering and Information Science; Vol. 14).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Rajkumar R, Zhang L, Sedov V, Mistry K. Supervised and Unsupervised Machine Learning Algorithms: An Empirical Evaluation. In Kerre EE, Martínez L, Li T, Montero J, Flores-Vidal P, editors, Intelligent Management of Data and Information in Decision Making. Singapore: World Scientific. 2024. p. 299-306. (World Scientific Proceedings Series on Computer Engineering and Information Science). Epub 2024 Jul 9. doi: 10.1142/9789811294631_0038