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SUPERVISED MACHINE LEARNING FOR SMART DATA ANALYSIS IN INTERNET OF THINGS ENVIRONMENT: AN OVERVIEW

Author(s)
MOHAMMED H. ALSHARIF Department of Electrical Engineering, College of Electronics and Information Engineering, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul, Korea
WILLIAM A. MOSIER Department of Biomedical Sciences, School of Health Sciences, Istanbul Gelisim University, Istanbul, Turkey
OSAMA AHMAD ALOMARI Department of Computer Engineering, Faculty of Engineering and Architecture, Istanbul Gelisim University, Istanbul, Turkey
KHALID YAHYA Department of Mechatronics Engineering, Istanbul Gelisim University, Avcılar, İstanbul, Turkey
Abstract
Machine learning techniques will contribution to making Internet of Things (IoT) applications that are considered the most significant sources of new data in the coming future more intelligent, where the systems will be able to access raw data from different resources over the network and analyze this information in order to extract knowledge. This study focuses on supervised machine learning techniques that is considered the main pillar of the IoT smart data analysis. This study includes reviews and discussions of substantial issues related to supervised machine learning techniques, highlighting the advantages and limitations of each algorithm, and discusses the research trends and recommendations for further study.
Publication Details
Page(s) 672-683
DOI DOI not available
Published Journal: Journal of Theoretical and Applied Information Technology, Volume: 98, Issue: 4, Year: 2020

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Keywords
Internet of Things, Big Data, supervised learning, Artificial Intelligence
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