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172 results for “machine learning algorithms”
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Research ArticleOpen accessIn the abstractMACHINE LEARNING APPROACHES IN IMPROVING SERVICE LEVEL AGREEMENT-BASED ADMISSION CONTROL FOR A SOFTWARE-AS-A-SERVICE PROVIDER IN CLOUDR. S. Mohana, P. ThangarajSoftware as a Service (SaaS) offers reliable access to software applications to the end users over the Internet without direct investment in infrastructure and software. SaaS providers utilize resources of internal data centres or rent resources from a public Infrastructure as a Service (IaaS) provider in order to serve their customers. Internal hosting can ample cost of administration and maintenance … …Journal of Computer Science, Vol. 9, Issue 10 · 5 Sep 2013 · 6,956 accessesView PDFCite
Research ArticleOpen accessIn the abstractEvaluation of Various Compiler Optimization Techniques Related to Mibench Benchmark ApplicationsJeyaraj Andrews, Thangappan SasikalaTuning compiler optimization for a given application of particular computer architecture is not an easy task, because modern computer architecture reaches higher levels of compiler optimization. These modern compilers usually provide a larger number of optimization techniques. By applying all these techniques to a given application degrade the program performance as well as more time consuming. The performance of the … …Journal of Computer Science, Vol. 9, Issue 6 · 6 Jun 2013 · 7,219 accessesView PDFCite
Research ArticleOpen accessIn the abstractArtificial Bee Colony Algorithm Integrated with Fuzzy C-mean Operator for Data ClusteringM. Krishnamoorthi, A. M. NatarajanClustering task aims at the unsupervised classification of patterns in different groups. To enhance the quality of results, the emerging swarm-based algorithms now-a-days become an alternative to the conventional clustering methods. In this study, an optimization method based on the swarm intelligence algorithm is proposed for the purpose of clustering. The significance of the proposed algorithm is that it uses … …Journal of Computer Science, Vol. 9, Issue 4 · 6 May 2013 · 6,299 accessesView PDFCite
Research ArticleOpen accessIn the abstractContent Based Image Retrieval of Ultrasound Liver Diseases Based on Hybrid ApproachR. Suganya, S. RajaramProblem statement: In the past few years, immense improvement was obtained in the field of Content-Based Image Retrieval (CBIR). Nevertheless, existing systems still fail when applied to medical image databases. Simple feature-extraction algorithms that operate on the entire image for characterization of color, texture, or shape cannot be related to the descriptive semantics of medical knowledge that is extracted from … …American Journal of Applied Sciences, Vol. 9, Issue 6 · 24 Mar 2012 · 7,643 accessesView PDFCite
Research ArticleOpen accessIn the abstractSteel Plates Faults Diagnosis with Data Mining ModelsMahmoud Fakhr, Alaa M. ElsayadProblem statement: Over the last two decades, Fault Diagnosis (FD) has a major importance to enhance the quality of manufacturing and to lessen the cost of product testing. Actually, quick and correct FD system helps to keep away from product quality problems and facilitates precautionary maintenance. FD may be considered as a pattern recognition problem. It has been gaining more … …Journal of Computer Science, Vol. 8, Issue 4 · 31 Jan 2012 · 11,378 accessesView PDFCite
Research ArticleOpen accessIn the abstractA New Cooperative Algorithm Based on PSO and K-Means for Data ClusteringMehdi Neshat, Shima Farshchian Yazdi, Daneyal Yazdani, Mehdi SargolzaeiProblem statement: Data clustering has been applied in multiple fields such as machine learning, data mining, wireless sensor networks and pattern recognition. One of the most famous clustering approaches is K-means which effectively has been used in many clustering problems, but this algorithm has some drawbacks such as local optimal convergence and sensitivity to initial points. Approach: Particle Swarm Optimization … …Journal of Computer Science, Vol. 8, Issue 2 · 19 Nov 2011 · 7,967 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 abstractComparative Evaluation of Phone Duration Models for Greek Emotional SpeechAlexandros Lazaridis, Vasiliki Bourna, Nikos FakotakisProblem statement: In this study we cope with the task of phone duration modeling for Greek emotional speech synthesis. Approach: Various well established machine learning techniques are applied for this purpose to an emotional speech database consisting of five archetypal emotions. The constructed phone duration prediction models are built on phonetic, morphosyntactic and prosodic features that can be extracted only … …Journal of Computer Science, Vol. 6, Issue 3 · 31 Mar 2010 · 7,065 accessesView PDFCite