Machine Learning Algorithms for Smart Data Analysis in Internet of Things Environment: Taxonomies and Research Trends
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Tarih
2020
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
MDPI, ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
Erişim Hakkı
info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivs 3.0 United States
Attribution-NonCommercial-NoDerivs 3.0 United States
Özet
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.
Açıklama
Document Information
Language:English
Accession Number: WOS:000516823700088
Anahtar Kelimeler
machine learning, artificial intelligence, supervised learning, unsupervised learning, big data, internet of things, NAIVE BAYES, SVM, CLASSIFIERS, MODEL
Kaynak
SYMMETRY-BASEL
WoS Q Değeri
Q2
Scopus Q Değeri
Q2
Cilt
12
Sayı
1
