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Machine Learning Algorithms for Smart Data Analysis in Internet of Things Environment: Taxonomies and Research Trends

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Department of Electrical Engineering, College of Electronics and Information Engineering, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul 05006, Korea
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Department of Electrical Engineering and Information Engineering, College of Engineering, Covenant University, Canaanland, Ota P.M.B 1023, Ogun State, Nigeria
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Department of Electrical and Electronics Engineering, Faculty of Engineering and Architecture, Istanbul Gelisim University, Avcılar, 34310 İstanbul, Turkey
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Department of Computer Engineering, Faculty of Engineering and Architecture, Istanbul Gelisim University, Avcılar, 34310 İstanbul, Turkey
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Author to whom correspondence should be addressed.
Symmetry 2020, 12(1), 88; https://doi.org/10.3390/sym12010088 (registering DOI)
Received: 10 December 2019 / Revised: 26 December 2019 / Accepted: 30 December 2019 / Published: 2 January 2020
Machine learning techniques will contribution towards making Internet of Things (IoT) symmetric applications among the most significant sources of new data in the future. In this context, network systems are endowed with the capacity to access varieties of experimental symmetric data across a plethora of network devices, study the data information, obtain knowledge, and make informed decisions based on the dataset at its disposal. This study is limited to supervised and unsupervised machine learning (ML) techniques, regarded as the bedrock of the IoT smart data analysis. This study includes reviews and discussions of substantial issues related to supervised and unsupervised machine learning techniques, highlighting the advantages and limitations of each algorithm, and discusses the research trends and recommendations for further study. View Full-Text
Keywords: machine learning; artificial intelligence; supervised learning; unsupervised learning; big data; internet of things machine learning; artificial intelligence; supervised learning; unsupervised learning; big data; internet of things
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Alsharif, M.H.; Kelechi, A.H.; Yahya, K.; Chaudhry, S.A. Machine Learning Algorithms for Smart Data Analysis in Internet of Things Environment: Taxonomies and Research Trends. Symmetry 2020, 12, 88.

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