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49 articles for “Support Vector Machine method (SVM)”
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Research ArticleOpen accessIn the abstractEnhanced Ensemble Prediction Algorithms for Detecting Faulty Modules in Object Oriented Systems Using Quality MetricsM. Punithavalli, C. NeelamegamThe high usage of software system poses high quality demand from users, which results in increased software complexity. To address these complexities, software quality engineering methods should be updated accordingly and enhance their quality assuring methods. Fault prediction, a sub-task of SQE, is designed to solve this issue and provide a strategy to identify faulty parts of a program, so … …Journal of Computer Science, Vol. 8, Issue 12 · 20 Dec 2012 · 6,435 accessesView PDFCite
Research ArticleOpen accessIn the abstractEvaluation on Score Reliability for Biometric Speaker Authentication SystemsDzati Athiar Ramli, Haryati Jaafar, Muhammad Hazim HasanProblem statement: Fusion weight tuning based on score reliability is imperative in order to ensure the performances of multibiometric systems are sustained. Approach: In this study, two variant of conditions i.e., different performances of individual subsystems and inconsistent quality of test samples are experimented to multibiometric systems. By applying multialgorithm scheme, two types of features extraction method i.e., Linear Predictive … …Journal of Computer Science, Vol. 8, Issue 9 · 16 Aug 2012 · 7,238 accessesView PDFCite
Research ArticleOpen accessIn the abstractSupport Vector Machine Based Red Palm Weevil (Rynchophorus Ferrugineous, Olivier) Recognition SystemGhulam Mubashar Hassan, Saleh Mufleh Al-SaqerProblem statement: Red palm weevil (Rynchophorus Ferrugineous, Oliveir) is an insect which threatens the existence of palm trees. The proposed research is to develop a RPW identification system using Support Vector Machine method. The problem is to extract image features from an image and using SVM to find out the existence of RPW in an image. Approach: Images are snapped … …American Journal of Agricultural and Biological Sciences, Vol. 7, Issue 1 · 24 Jan 2012 · 7,734 accessesView PDFCite
Research ArticleOpen accessIn the abstractEfficient 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 · 7,441 accessesView PDFCite
Research ArticleOpen accessIn the abstractCancer 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 · 7,593 accessesView PDFCite
Research ArticleOpen accessIn the abstractFeature Subset Selection for Hot Method Prediction using Genetic Algorithm wrapped with Support Vector MachinesSandra Johnson, Valli ShanmugamProblem statement: All compilers have simple profiling-based heuristics to identify and predict program hot methods and also to make optimization decisions. The major challenge in the profile-based optimization is addressing the problem of overhead. The aim of this work is to perform feature subset selection using Genetic Algorithms (GA) to improve and refine the machine learnt static hot method predictive … …Journal of Computer Science, Vol. 7, Issue 5 · 7 May 2011 · 7,234 accessesView PDFCite
Research ArticleOpen accessIn the abstractHuman Behavior Classification Using Multi-Class Relevance Vector MachineB. Yogameena, S. Veera Lakshmi, M. Archana, S. Raju AbhaikumarProblem statement: In computer vision and robotics, one of the typical tasks is to identify specific objects in an image and to determine each object’s position and orientation relative to coordinate system. This study presented a Multi-class Relevance Vector machine (RVM) classification algorithm which classifies different human poses from a single stationary camera for video surveillance applications. Approach: First the … …Journal of Computer Science, Vol. 6, Issue 9 · 30 Sep 2010 · 7,390 accessesView PDFCite
Research ArticleOpen accessIn the abstractSupport Vector Machine-Based Human Behavior Classification in Crowd through Projection and Star SkeletonizationB. Yogameena, E. Komagal, M. Archana, S. Raju AbhaikumarProblem statement: Detection of individual’s abnormal human behaviors in the crowd has become a critical problem because in the event of terror strikes. This study presented a real-time video surveillance system which classifies normal and abnormal behaviors in crowds. The aim of this research was to provide a system which can aid in monitoring crowded urban environments. Approach: The proposed … …Journal of Computer Science, Vol. 6, Issue 9 · 30 Sep 2010 · 7,557 accessesView PDFCite
Research ArticleOpen accessIn the abstractPrediction of End-of-Life Strategies for Household Equipments Using Artificial IntelligentM. M. Noor, K. Kadirgama, Aidy Ali et al.Problem statement: Environment issue on the dumping of used household product is a big challenge nowadays. Towards green design, life cycle of a product is very crucial. This study discussed on recycling strategies which include reuse, service, remanufacture and recycle with or without disassembly by using Support Vector Machine Method (SVM). Approach: In early stage of prediction, the input parameters … …American Journal of Applied Sciences, Vol. 6, Issue 10 · 31 Oct 2009 · 7,931 accessesView PDFCite
Research ArticleOpen accessIn the abstractSupport Vector Machine for Discrimination Between Fault and Magnetizing Inrush Current in Power TransformerV. Malathi, N. S. MarimuthuThis study presents a novel technique based on Support Vector Machine (SVM) for the classification of transient phenomena in power transformer. The SVM is a powerful method for statistical classification of data. The input data to this SVM for training comprises fault current and magnetizing inrush current. SVM classifier produces significant accuracy for classification of transient phenomena in power transformer. …Journal of Computer Science, Vol. 3, Issue 11 · 30 Nov 2007 · 6,737 accessesView PDFCite