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review of machine learning algorithms

In this review paper, we present an analysis of CC security threats, issues, and solutions that utilized one or several ML algorithms. Machine learning (ML) is the investigation of computer algorithms that improve naturally through experience. Department of Computer Science, University of Engineering and Technology, Taxila 47080, Pakistan, School of Software, Dalian University of Technology, Dalian 116000, China, Department of Computer Science, Abasyn University, Peshawar 25000, Pakistan, Department of Electronics Engineering, Kyung Hee University, Yong-in 17104, Korea, Department of Computer Science and Engineering, Sejong University, Seoul 05006, Korea. A review of supervised machine learning algorithms Abstract: Supervised machine learning is the construction of algorithms that are able to produce general patterns and hypotheses by using externally supplied instances to predict the fate of future instances. The lack of shared datasets and a standard definition and classification of NFRs are among the open challenges. In summary, the main findings of the Edge computing is an evolving computing paradigm that brings computation and information storage nearer to the end-users to improve response times and spare transmission capacity. These The Ghost in the Machine … to name a few. Machine learning (ML) is the investigation of computer algorithms that improve naturally through experience. Find support for a specific problem on the support section of our website. The review finds 7 different performance measures, of which precision and recall are most popular. J. Machine-learning algorithms use statistics to find patterns in massive* amounts of data. Since deep neural networks were developed, they have made huge contributions to everyday lives. In this review paper, we present an analysis of CC security threats, issues, and solutions that utilized one or several ML algorithms. We applied ML approaches to a … Machine learning requires a large, accurate data set to help train algorithms. Here is an overview of the most common … 9: 1379. In this review paper, we present an analysis of CC security threats, issues, and solutions that utilized one or several ML Directed by three research questions, this article aims to understand what ML algorithms are used in these approaches, how these algorithms work and how they are evaluated. The aim is to achieve a high-performing algorithm comparable to human screening that can reduce human resources required for carrying out this step of a systematic review. Our dedicated information section provides allows you to learn more about MDPI. Authors to whom correspondence should be addressed. The statements, opinions and data contained in the journal, © 1996-2020 MDPI (Basel, Switzerland) unless otherwise stated. This is an open access article distributed under the, Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. ; Suh, D.Y. Machine learning, a part of AI (artificial intelligence), is used in the designing of algorithms based on the recent trends of data. And data, here, encompasses a lot of things—numbers, words, images, clicks, what have you. Review of Deep Learning Algorithms and Architectures Abstract: Deep learning (DL) is playing an increasingly important role in our lives. Published by Elsevier Ltd. https://doi.org/10.1016/j.eswax.2019.100001. Kotsiantis SB (2007) Supervised machine learning: a review of classification techniques. Moreover, we enlist future research directions to secure CC models. In the recent past, machine learning has been proven to be susceptible to carefully crafted adversarial examples. Machine learning is the name used to describe a collection of computer algorithms that can learn and improve by gathering information while they are running. Then, we compare the performance of each technique based on their features, advantages, and disadvantages. ML-based approaches have the potential in the classification and identification of NFRs. Machine learning is a field of computer science which gives computers an ability to learn without being explicitly programmed. Multiple requests from the same IP address are counted as one view. ; Raza, S.M. ; Amin, Rashid; Shaukat, M. W.; Raza, Syed M.; Suh, Doug Y.; Piran, Md. CC recently has emerged as a set of public and private datacenters that offers the client a single platform across the Internet. ; Mehmood, M.; Shah, S.B.H. ScienceDirect ® is a registered trademark of Elsevier B.V. ScienceDirect ® is a registered trademark of Elsevier B.V. A review of machine learning algorithms for identification and classification of non-functional requirements, Requirements identification Requirements classification. (1) 16 different ML algorithms are found in these approaches; of which supervised learning algorithms are most popular. ML algorithms are primarily employed at the screening stage in the systematic review process. The use of ML in RE opens up exciting opportunities to develop novel expert and intelligent systems to support RE tasks and processes.

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