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33 results for “Supervised Learning Algorithm”
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Research ArticleOpen accessIn the abstractMachine Learning Oceanographic Data for Prediction of the Potential of Marine ResourcesDenny Arbahri, Oky Dwi Nurhayati, Imam MuditaMarine data and information are very important for human survival, therefore this data and information is attractive to investors because of the potential economic value. This data and information has been difficult to obtain, the solution to overcome this is by analyzing oceanographic data for 2009-2019 collected from the marine database belonging to the Agency for the Study and Application … …Journal of Computer Science, Vol. 20, Issue 2 · 8 Jan 2024 · 5,970 accessesView PDFCite
Research ArticleOpen accessIn the abstractCybersecurity Mechanism for Automatic Detection of IoT Intrusions Using Machine LearningCheikhane Seyed, MBaye Kebe, Mohamed El Moustapha El Arby et al.This article proposes an ML-based cyber security mechanism to optimize intrusion detection that attacks internet objects (IoT). Our approach consists of bringing together several learning methods namely supervised learning, unsupervised learning and reinforcement learning within the same Canvas. The objective is to choose among them the most optimal for classifying and predicting attacks while minimizing the impact linked to the … …Journal of Computer Science, Vol. 20, Issue 1 · 11 Dec 2023 · 6,176 accessesView PDFCite
Review ArticleOpen accessIn the abstractCrime Prediction Using Machine Learning: A Comparative AnalysisAbdulrahman Alsubayhin, Muhammad Ramzan, Bander AlzahraniIn the past few years, Machine Learning (ML) methods have acquired extensive attention from researchers and even criminology practitioners for their potential in crime prediction and crime forecast. To date, many research studies have already been performed on crime prediction using machine learning techniques. Some common methods that have been used include KNNs, Decision trees, Naïve Bayes, and random forest, … …Journal of Computer Science, Vol. 19, Issue 9 · 29 Aug 2023 · 8,063 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Integrated Machine Learning Model for Heart Disease Classification and CategorizationSrikanth Meda, Raveendrababu BhogapathiProgressions in the coordination among the machine learning algorithms, helped to achieve high accuracy and reliability in decision-making systems. Due to the impact and importance of heart diseases in real life, designing the efficient heart disease prediction model become a pivotal aspect today. Former research scholars applied the popular supervised machine learning models like Decision Trees, Naïve Bayes, ANN's, and … …Journal of Computer Science, Vol. 18, Issue 4 · 19 Apr 2022 · 6,535 accessesView PDFCite
Research ArticleOpen accessIn the abstractSoft Marking Scheme of SVM Hierarchical Classifiers for Attack ClassificationAzizi Abdullah, Warhamni Jani@MokhtarClassification is a predictive modelling problem that involves assigning a class label to an instance correctly. There exist several strategies in machine learning to deal with the multi-class classification problems for attack detection. One of the popular strategies is the one-vs-one that decomposes the multi-class problem into multiple binary ones. The approach has been applied in many popular supervised learning … …Journal of Computer Science, Vol. 17, Issue 9 · 27 Sep 2021 · 6,000 accessesView PDFCite
Research ArticleOpen accessIn the abstractSQL Generation from Natural Language: A Sequence-to-Sequence Model Powered by the Transformers Architecture and Association RulesYoussef Mellah, Abdelkader Rhouati, El Hassane Ettifouri et al.Using Natural Language (NL) to interacting with relational databases allows users from any background to easily query and analyze large amounts of data. This requires a system that understands user questions and automatically converts them into structured query language such as SQL. The best performing Text-to-SQL systems use supervised learning (usually formulated as a classification problem) by approaching this task … …Journal of Computer Science, Vol. 17, Issue 5 · 23 May 2021 · 10,027 accessesView PDFCite
Research ArticleOpen accessIn the abstractLeafsnapNet: An Experimentally Evolved Deep Learning Model for Recognition of Plant Species based on Leafsnap Image DatasetEmmanuel Adetiba et al.Plants are very important living organisms on earth because humans and animals depend on them for nutrition, oxygen, medicine and balance in the ecosystem. Therefore, plant species recognition is critical to the improvement of agricultural productivity, mitigation of climate change and the discovery of new medicinal plants. However, species recognition has remained a difficult task even for trained botanists, because … …Journal of Computer Science, Vol. 17, Issue 3 · 1 Apr 2021 · 7,956 accessesView PDFCite
Research ArticleOpen accessIn the abstractSocial Media Sentiment Analysis: The Hajj Tweets Case StudyMohammad Ashraf Ottom, Khalid M.O. NaharAbout forty five percent of the world's population use social networks, thinking of using these platforms seemed to find people's opinions and feelings on various topics. Companies that offer their services and products to customers focus on the subject for future improvement. Thus, serious thinking began to analyze the views of people across different social platforms and also to develop … …Journal of Computer Science, Vol. 17, Issue 3 · 20 Mar 2021 · 7,759 accessesView PDFCite
Research ArticleOpen accessIn the abstractFall Detection Using the Histogram of Oriented Gradients and Decision-Based FusionMohamed Maher Ben Ismail, Arwa AlGabas, Ouiem BchirAs the number of fall incidents among elderly people and patients are continuously growing, researches boosted their researches to propose efficient automatic fall detection systems. In particular, they formulated the fall detection problem as a supervised learning task where some visual features are extracted from the video frames and used to automatically identify the position of a human as “Fall” … …Journal of Computer Science, Vol. 16, Issue 2 · 26 Feb 2020 · 7,500 accessesView PDFCite
Review ArticleOpen accessIn the abstractWord Sense Disambiguation: Survey StudyAhmed H. Aliwy, Hawraa A. TaherThe process of identifying the correct sense of a given word in a particular sentence is called Word Sense Disambiguation (WSD). It is complex problem because it involves drawing knowledge from various sources. Significant amount of effort has been put into resolving this problem in machine learning since its inception but the toil is still ongoing. Many techniques were used … …Journal of Computer Science, Vol. 15, Issue 7 · 26 Jul 2019 · 8,388 accessesView PDFCite