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

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dc.authoridhttps://orcid.org/0000-0002-9321-6956en_US
dc.authoridhttps://orcid.org/0000-0002-0792-7031en_US
dc.authoridhttps://orcid.org/0000-0001-8579-5444en_US
dc.contributor.authorAlsharif, Mohammed H.
dc.contributor.authorKelechi, Anabi Hilary
dc.contributor.authorChaudhry, Shehzad Ashraf
dc.date.accessioned2020-05-18T00:24:35Z
dc.date.available2020-05-18T00:24:35Z
dc.date.issued2020en_US
dc.departmentMühendislik ve Mimarlık Fakültesien_US
dc.descriptionDocument Information Language:English Accession Number: WOS:000516823700088en_US
dc.description.abstractMachine 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.en_US
dc.identifier.doi10.3390/sym12010088en_US
dc.identifier.issn2073-8994
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-85083439425en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://hdl.handle.net/11363/2148
dc.identifier.urihttps://doi.org/
dc.identifier.volume12en_US
dc.identifier.wosWOS:000516823700088en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherMDPI, ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLANDen_US
dc.relation.ispartofSYMMETRY-BASELen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subjectmachine learningen_US
dc.subjectartificial intelligenceen_US
dc.subjectsupervised learningen_US
dc.subjectunsupervised learningen_US
dc.subjectbig dataen_US
dc.subjectinternet of thingsen_US
dc.subjectNAIVE BAYESen_US
dc.subjectSVMen_US
dc.subjectCLASSIFIERSen_US
dc.subjectMODELen_US
dc.titleMachine Learning Algorithms for Smart Data Analysis in Internet of Things Environment: Taxonomies and Research Trendsen_US
dc.typeArticleen_US

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