Challenges in supervised and unsupervised learning: a comprehensive overview
Data science and machine learning are at the forefront of modern technological advancements, promising automated insights, predictions, and decision-making. Supervised and unsupervised learning are pivotal paradigms within this dynamic landscape, each presenting its unique challenges. This article p...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Insight Society
2024
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| Online Access: | http://psasir.upm.edu.my/id/eprint/113099/ http://psasir.upm.edu.my/id/eprint/113099/1/113099.pdf |
| _version_ | 1848866127161065472 |
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| author | Almuqati, Mohammed Tuays Sidi, Fatimah Mohd Rum, Siti Nurulain Zolkepli, Maslina Ishak, Iskandar |
| author_facet | Almuqati, Mohammed Tuays Sidi, Fatimah Mohd Rum, Siti Nurulain Zolkepli, Maslina Ishak, Iskandar |
| author_sort | Almuqati, Mohammed Tuays |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Data science and machine learning are at the forefront of modern technological advancements, promising automated insights, predictions, and decision-making. Supervised and unsupervised learning are pivotal paradigms within this dynamic landscape, each presenting its unique challenges. This article provides a comprehensive overview of the multifaceted challenges inherent to both supervised and unsupervised learning. This article reviews research studies published between 2019 and 2023. This article discusses the challenges of supervised and unsupervised learning. In supervised learning, challenges include data labeling, overfitting, limited generalization, and balancing mistake equivalence and decision-making goals. In unsupervised learning, difficulties encompass issues like overfitting, choosing the appropriate algorithm, and interpreting results. This includes evaluating the quality of clustering, deciding the optimal number of clusters, and managing noise and outliers. The article aims to provide insights into these challenges, enhancing the understanding of machine learning for both novices and experts. Researchers and practitioners constantly evolve their methods and tools to overcome these complexities. This article is a valuable reference for researchers and experts in the field, empowering them to navigate these challenges confidently. As technology advances, a thorough understanding of these challenges is essential for unlocking the full potential of these powerful tools. Finally, several recommendations were given to guide future researchers in applying machine learning in the journey of data-driven discovery and automation, offering challenges and opportunities for those who embark on it. |
| first_indexed | 2025-11-15T14:15:39Z |
| format | Article |
| id | upm-113099 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T14:15:39Z |
| publishDate | 2024 |
| publisher | Insight Society |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1130992024-11-15T08:19:38Z http://psasir.upm.edu.my/id/eprint/113099/ Challenges in supervised and unsupervised learning: a comprehensive overview Almuqati, Mohammed Tuays Sidi, Fatimah Mohd Rum, Siti Nurulain Zolkepli, Maslina Ishak, Iskandar Data science and machine learning are at the forefront of modern technological advancements, promising automated insights, predictions, and decision-making. Supervised and unsupervised learning are pivotal paradigms within this dynamic landscape, each presenting its unique challenges. This article provides a comprehensive overview of the multifaceted challenges inherent to both supervised and unsupervised learning. This article reviews research studies published between 2019 and 2023. This article discusses the challenges of supervised and unsupervised learning. In supervised learning, challenges include data labeling, overfitting, limited generalization, and balancing mistake equivalence and decision-making goals. In unsupervised learning, difficulties encompass issues like overfitting, choosing the appropriate algorithm, and interpreting results. This includes evaluating the quality of clustering, deciding the optimal number of clusters, and managing noise and outliers. The article aims to provide insights into these challenges, enhancing the understanding of machine learning for both novices and experts. Researchers and practitioners constantly evolve their methods and tools to overcome these complexities. This article is a valuable reference for researchers and experts in the field, empowering them to navigate these challenges confidently. As technology advances, a thorough understanding of these challenges is essential for unlocking the full potential of these powerful tools. Finally, several recommendations were given to guide future researchers in applying machine learning in the journey of data-driven discovery and automation, offering challenges and opportunities for those who embark on it. Insight Society 2024 Article PeerReviewed text en cc_by_nc_sa_4 http://psasir.upm.edu.my/id/eprint/113099/1/113099.pdf Almuqati, Mohammed Tuays and Sidi, Fatimah and Mohd Rum, Siti Nurulain and Zolkepli, Maslina and Ishak, Iskandar (2024) Challenges in supervised and unsupervised learning: a comprehensive overview. International Journal on Advanced Science, Engineering and Information Technology, 14 (4). pp. 1449-1455. ISSN 2088-5334; eISSN: 2460-6952 https://ijaseit.insightsociety.org/index.php/ijaseit/article/view/20191 10.18517/ijaseit.14.4.20191 |
| spellingShingle | Almuqati, Mohammed Tuays Sidi, Fatimah Mohd Rum, Siti Nurulain Zolkepli, Maslina Ishak, Iskandar Challenges in supervised and unsupervised learning: a comprehensive overview |
| title | Challenges in supervised and unsupervised learning: a comprehensive overview |
| title_full | Challenges in supervised and unsupervised learning: a comprehensive overview |
| title_fullStr | Challenges in supervised and unsupervised learning: a comprehensive overview |
| title_full_unstemmed | Challenges in supervised and unsupervised learning: a comprehensive overview |
| title_short | Challenges in supervised and unsupervised learning: a comprehensive overview |
| title_sort | challenges in supervised and unsupervised learning: a comprehensive overview |
| url | http://psasir.upm.edu.my/id/eprint/113099/ http://psasir.upm.edu.my/id/eprint/113099/ http://psasir.upm.edu.my/id/eprint/113099/ http://psasir.upm.edu.my/id/eprint/113099/1/113099.pdf |