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42 articles for “Supervised Algorithm”
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Research ArticleOpen accessIn the abstractDetection of Rust Emergence in Coffee Plantations using Data Mining: A Systematic ReviewLenin Quiñones Huatangari, Candy Lisbeth Ocaña Zúñiga, Annick Estefany Huaccha Castillo et al.Hemileia vastatrix is a fungus that causes coffee rust disease and, depending on the level of severity, reduces the photosynthetic capacity of the plant and of new shoots, leading to low coffee yields and even death; its symptoms are visible on the leaf. Systems based on computer algorithms have been developed to predict diseases and pests in coffee. The objective … …OnLine Journal of Biological Sciences, Vol. 22, Issue 2 · 31 Mar 2022 · 8,022 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
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 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 abstractUnfair Reviews Detection on Amazon Reviews using Sentiment Analysis with Supervised Learning TechniquesElshrif Ibrahim Elmurngi, Abdelouahed GherbiReputation and trust are significantly important and play a pivotal role in enabling multiple parties to establish relationships that achieve mutual benefit especially in an E-Commerce (EC) environment. There are several factors negatively affecting the sight of customers and sellers in terms of reputation. For instance, lack of credibility in providing feedback reviews, by which users might create phantom feedback … …Journal of Computer Science, Vol. 14, Issue 5 · 14 May 2018 · 9,882 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
Literature ReviewOpen accessIn the abstractEfficient Morphometric Techniques in Alzheimer’s Disease Detection: Survey and ToolsVinutha N., P. Deepa Shenoy, K.R. VenugopalThe development of advance techniques in the multiple fields such as image processing, data mining and machine learning are required for the early detection of Alzheimer’s Disease (AD) and to prevent the progression of the disease to the later stages. The longitudinal and cross sectional images of elderly subjects were obtained from the standard datasets like ADNI, OASIS, MIRIAD and … …Neuroscience International, Vol. 7, Issue 2 · 4 Oct 2017 · 8,450 accessesView PDFCite
EditorialOpen accessIn the abstractData Mining in Time Series: Current Study and Future TrendTan Yan, Liudmila Ulanova, Ye Ouyang, Fengyuan XuTime series represent sequences of data points where usually their order is defined by the time when they were recorded. Thus, virtually any sequential recordings can be stored as time series: Stock prices, weather conditions, physical system parameters change, product quality monitoring, etc. This leads to ubiquity of time series in all scientific and practical fields (Esling and Agon, 2012); … …Journal of Computer Science, Vol. 10, Issue 12 · 26 Jan 2015 · 8,756 accessesView PDFCite
Research ArticleOpen accessIn the abstractHALF OF THRESHOLD ALGORITHM: AN ENHANCED LINEAR ADAPTIVE SKIPPING TRAINING ALGORITHM OR MULTILAYER FEEDFORWARD NEURAL NETWORKSManjula Devi Ramasamy, Kuppuswami Subbaraya GounderMultilayer Feed Forward Neural Network (MFNN) has been successfully administered architectures for solving a wide range of supervised pattern recognition tasks. The most problematic task of MFNN is training phase which consumes very long training time on very huge training datasets. An enhanced linear adaptive skipping training algorithm for MFNN called Half of Threshold (HOT) is proposed in this research … …American Journal of Applied Sciences, Vol. 11, Issue 1 · 22 Nov 2013 · 7,016 accessesView PDFCite