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41 results for “Support Vector Machines (SVM)”
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Research ArticleOpen accessIn the abstractMyocardial-Infraction Based on Intelligent TechniquesIbrahim Abdulrab AhmedProblem statement: Heart disease is the leading cause of death in the world. One of the most common types of heart diseases is Myocardial-Infraction. The ability to automatically identify Myocardial-Infraction from cardiac profiles test is important for clinical diagnosis and treatment. Approach: The aim of this study is to see whether the heart is healthy or not, in another words … …American Journal of Applied Sciences, Vol. 7, Issue 3 · 31 Mar 2010 · 7,609 accessesView PDFCite
Research ArticleOpen accessIn the abstractUnbalance Quantitative Structure Activity Relationship Problem Reduction in Drug DesignD. Pugazhenthi, S. P. RajagopalanProblem statement: Activities of drug molecules can be predicted by Quantitative Structure Activity Relationship (QSAR) models, which overcome the disadvantage of high cost and long cycle by employing traditional experimental methods. With the fact that number of drug molecules with positive activity is rather fewer than that with negatives, it is important to predict molecular activities considering such an unbalanced … …Journal of Computer Science, Vol. 5, Issue 10 · 31 Oct 2009 · 6,707 accessesView PDFCite
Research ArticleOpen accessIn the abstractChi Square Feature Extraction Based Svms Arabic Language Text Categorization SystemAbdelwadood Moh’d A MESLEHThis paper aims to implement a Support Vector Machines (SVMs) based text classification system for Arabic language articles. This classifier uses CHI square method as a feature selection method in the pre-processing step of the Text Classification system design procedure. Comparing to other classification methods, our system shows a high classification effectiveness for Arabic data set in term of F-measure … …Journal of Computer Science, Vol. 3, Issue 6 · 30 Jun 2007 · 11,067 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordPandemic Analysis and Preparedness Using a Three Layer Machine Learning ApproachArtika Singh, Manisha JailiaOutbreak analysis provides research-based information and data to enable scientific decision-making to manage an effective response to a pandemic. Pandemic analysis has its own set of challenges, such as limited data, the need for real time analysis, and the complexity of outbreak patterns. This study proposes a hybrid approach to manage such a spread through a 3-layer machine learning-based outbreak … …Journal of Computer Science, Vol. 22, Issue 11 · 15 Oct 2026 · 632 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordImproved SVM with Hyperparameter Tuning for Fake News DetectionAtcharaporn Nachaithong, Kittipol WisaengIn today’s digital age, accessing information has become effortless. An abundance of resources is available online, from trustworthy news outlets providing factual information to unverified opinions shared by anonymous individuals. With the advent of modern technology, social media platforms have revolutionized interaction and staying informed, providing instant access to news and information related to a wide range of topics. They … …Journal of Computer Science, Vol. 20, Issue 10 · 28 Aug 2024 · 5,645 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordSoft 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 · 6,006 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordCost-based Reweighting for Principal Lq Support Vector Machines for Sufficient Dimension ReductionAndreas ArtemiouIn this work we try to address the imbalance of the number of points which naturally occurs when slicing the response in Sufficient Dimension Reduction methods (SDR). Specifically, some recently proposed support vector machine based (SVM-based) methodology suffers a lot more due to the properties of the SVM algorithm. We target a recently proposed algorithm called Principal LqSVM and we … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 5 Sep 2019 · 7,260 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordCAROTID PLAQUE CLASSIFICATION USING CONTOURLET FEATURES AND SUPPORT VECTOR MACHINESM. Thangavel, M. Chandrasekaran, M. MadheswaranThe aim of this study is to propose a suitable and reliable system for better diagnosis and treatment of carotid diseases. In this study, Computer Aided Diagnosis (CAD) system has been proposed for classifying carotid artery plaques using Contourlet features. Carotid images have been acquired for 124 subjects with symptoms (Amaurosis Fugax, Stroke or Transient Ischemic Attack) and 133 subjects … …Journal of Computer Science, Vol. 10, Issue 9 · 15 Apr 2014 · 6,781 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordEfficient Classification of Cancer using Support Vector Machines and Modified Extreme Learning Machine based on Analysis of Variance FeaturesA. Bharathi, A.M. NatarajanProblem statement: The primary objective is to propose efficient cancer classification techniques which provide reliable and significant classification accuracy. To achieve this primary research goal is to find the smallest set of genes that can ensure high accuracy in classification using supervised machine learning algorithms. The significance of finding the minimum subset is three fold: (a) The computational burden and … …American Journal of Applied Sciences, Vol. 8, Issue 12 · 22 Oct 2011 · 7,446 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordCancer Classification using Support Vector Machines and Relevance Vector Machine based on Analysis of Variance FeaturesA. Bharathi, A.M. NatarajanProblem statement: The objective of this study is, to find the smallest set of genes that can ensure highly accurate classification of cancer from micro array data by using supervised machine learning algorithms. The significance of finding the minimum subset is three fold: The computational burden and noise arising from irrelevant genes are much reduced; the cost for cancer testing … …Journal of Computer Science, Vol. 7, Issue 9 · 25 Jul 2011 · 7,596 accessesView PDFCite