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480 results for “Machine Learning (ML)”
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Research ArticleOpen accessIn the abstractPARALLEL IMPLEMENTATION OF EXPECTATION-MAXIMISATION ALGORITHM FOR THE TRAINING OF GAUSSIAN MIXTURE MODELSG. F. Araújo, H. T. Macedo, M. T. Chella et al.Most machine learning algorithms need to handle large data sets. This feature often leads to limitations on processing time and memory. The Expectation-Maximization (EM) is one of such algorithms, which is used to train one of the most commonly used parametric statistical models, the Gaussian Mixture Models (GMM). All steps of the algorithm are potentially parallelizable once they iterate over … …Journal of Computer Science, Vol. 10, Issue 10 · 9 Jul 2014 · 6,937 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 abstractRadial Basis Function Network Dependent Exclusive Mutual Interpolation for Missing Value ImputationR. S. Somasundaram, R. NedunchezhianThe success of data mining relies on the purity of the data set. Before performing the data mining, the data has to be cleaned. An unprocessed data set may contain noisy or missing values which is a critical research issue in the pre-processing stage. Imputation methods are being used to solve the missing value problems. In this proposed work, a … …Journal of Computer Science, Vol. 9, Issue 3 · 24 Apr 2013 · 7,002 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Overview of Research Challenges for Classification of Cardiotocogram DataC. Sundar, M. Chitradevi, G. GeetharamaniCardiotocography (CTG) is a simultaneous recording of Fetal Heart Rate (FHR) and Uterine Contractions (UC). The most common diagnostic techniques to evaluate maternal and fetal well-being during pregnancy and before delivery. By observing the Cardiotocography trace patterns doctors can understand the state of the fetus. There are several signal processing and computer programming based techniques for interpreting a typical Cardiotocography … …Journal of Computer Science, Vol. 9, Issue 2 · 2 Apr 2013 · 7,827 accessesView PDFCite
Research ArticleOpen accessIn the abstractHome Users Security and the Web Browser Inbuilt Settings, Framework to Setup it AutomaticallyMohammed Serrhini, Abdelazziz Ait MoussaWe are living in the electronic age where electronic transactions such as e-mail, e-banking, e-commerce and e-learning becoming more and more prominent. To access online for this services, the web browser is today’s almost unique software used. These days’ hackers know that browsers are installed into all computers and can be used to compromise a machine by distributing malware via … …Journal of Computer Science, Vol. 9, Issue 2 · 1 Apr 2013 · 6,806 accessesView PDFCite
Research ArticleOpen accessIn the abstractArabic Named Entity Recognition Using Artificial Neural NetworkNaji F. Mohammed, Nazlia OmarProblem statement: Named Entity Recognition (NER) is a task to identify proper names as well as temporal and numeric expressions, in an open-domain text. The NER task can help to improve the performance of various Natural Language Processing (NLP) applications such as Information Extraction (IE), Information Retrieval (IR) and Question Answering (QA) tasks. This study discusses on the Named Entity … …Journal of Computer Science, Vol. 8, Issue 8 · 16 Jul 2012 · 8,676 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 abstractA New Algorithm for Fractal Coding Using Self Organizing MapS. Bhavani, k. ThanushkodiProblem statement: In medical imaging, lossy compression schemes are generally not used due to possible loss of useful clinical information and also degradations may result in lossy compression owing to operations like enhancement. As the medical images are huge in size a good lossy compression technology is required to store them in medical archives in an economical manner. There is … …Journal of Computer Science, Vol. 8, Issue 6 · 15 Mar 2012 · 7,583 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 abstractDetection of Aberrant Data Points for an effective Effort Estimation using an Enhanced Algorithm with Adaptive FeaturesS. Malathi, S. SridharProblem statement: The spiraling growth of IT industry has witnessed an unprecedented change in the software development paradigm, from algorithmic models to machine learning techniques. At present, there are no standard methods to predict the accuracy of software cost estimation, which is an important goal of the software community. Approach: This study proposes a simple and systematic algorithmic procedure for … …Journal of Computer Science, Vol. 8, Issue 2 · 21 Nov 2011 · 7,094 accessesView PDFCite