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A Literature Survey on Support Vector Machine Models and Applications |
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PP: 31-40 |
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doi:10.18576/ncmse/040104
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Author(s) |
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Ahmed I. Taloba,
Osama R. Shahin,
Rasha M. Abd El-Aziz,
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Abstract |
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| Artificial intelligence has been gaining importance in the daily lives of people. Machine learning forms a part of artificial intelligence, which has many endeavors in today’s scenario. It assists the organizations for performing tasks in a better manner and with the aid of deep learning and machine learning; artificial intelligence becomes smarter with an increased efficiency over time. One among the eminent part of machine learning is the Support Vector Machines (SVM). The eminent objective of support vector machines (SVM) is for correcting and classifying the unseen data. This paper of research rolls around the survey of literature, on the models and applications of the support vector machines. The paper provides insights for solving complex transformations of data handled in real-world endeavors. The study acts as a base for research on application of the suitable SVM model for the suitable application employed in machine learning. The paper maps out the latest research associated with the support vector machines with a suitable disquisition review. The paper focuses on identifying the latest research associated with support vector machines with a literature review following questions of research such as; the application of SVMs in which areas of research; the eminent applications associated with the classification of SVMs and the algorithms or models utilized in SVMs. It also deals with the models of SVM such as TSVM, LSSVM, PSVM, etc. Finally, the execution of these models in various SVM applications is discussed in this paper.
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