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49 results for “Bayesian Method”
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Research ArticleOpen accessIn the abstractObesity Level Estimation Software based on Decision TreesEduardo De-La-Hoz-Correa, Fabio E. Mendoza-Palechor, Alexis De-La-Hoz-Manotas et al.Obesity has become a global epidemic that has doubled since 1980, with serious consequences for health in children, teenagers and adults. Obesity is a problem has been growing steadily and that is why every day appear new studies involving children obesity, especially those looking for influence factors and how to predict emergence of the condition under these factors. In this … …Journal of Computer Science, Vol. 15, Issue 1 · 8 Jan 2019 · 14,100 accessesView PDFCite
Research ArticleOpen accessIn the abstractMCMC-Fuzzy: A Fuzzy Metric Applied to Bayesian Network Structure LearningBeatriz Wilges, Ademar Crotti Junior, Silvia Modesto NassarBayesian network structure learning is considered a complex task as the number of possible structures grows exponentially with the number of variables. Two main methods are used for Bayesian network structure learning: Conditional independence, a method in which a structure is created consistently with independence tests performed on data; and the heuristic search method that explores the structure space. Hybrid … …Journal of Computer Science, Vol. 14, Issue 8 · 24 Aug 2018 · 8,243 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comparative Study of Data Mining approaches for Bag of Visual Words Based Image ClassificationSahar Abd El Hameed Mokhtar, Heba Ahmed ElnemrImage classification is one of the most significant and challenging tasks in computer vision. The goal of this task is to build a system that is capable to reveal an image label within a collection of different image categories. This paper presents and discusses the application of various data mining techniques for image classification based on Bag of Visual Words … …Journal of Computer Science, Vol. 14, Issue 1 · 12 Jan 2018 · 7,983 accessesView PDFCite
Research ArticleOpen accessIn the abstractStock Trading Using PE Ratio Based on Bayesian InferenceHaizhen Wang, Ratthachat Chatpatanasiri, Pairote SattayathamThe Price Earnings (PE) ratio is one of the most widely applied tool for the firm valuation in a security market. Unfortunately, recent academic developments in financial econometrics and machine learning have rarely looked at this tool. In the paper, we propose to formalize a process of fundamental PE ratio estimation by employing Dynamic Bayesian Network (DBN) methodology. Forward-backward inference … …Journal of Mathematics and Statistics, Vol. 13, Issue 3 · 29 Sep 2017 · 7,425 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Algorithm for Determining the Number of Mixture Components on the Bayesian Mixture Model Averaging for Microarray DataAni Budi Astuti, Nur Iriawan, Irhamah, Heri KuswantoThe major challenges on the statistical analysis of microarray data are the limited availability of samples, large number of measured variables and the complexity of distribution of the data obtained (e.g., multimodal). These phenomena could be considered in Bayesian method, used Bayesian Mixture Model (BMM) methods and Bayesian Model Averaging (BMA) methods. Modeling of Bayesian Mixture Model Averaging (BMMA) for … …Journal of Mathematics and Statistics, Vol. 11, Issue 2 · 28 Sep 2015 · 7,136 accessesView PDFCite
Research ArticleOpen accessIn the abstractAmeliorate Fuzzy C-Means: An Ameliorate Fuzzy C-Means Clustering Algorithm for CT-Lung Image SegmentationJ. Bridget Nirmala, S. GowriEffective and efficient image segmentation acts as a preliminary stage for the computer-aided diagnosis of medical images. For image segmentation, many FCM-based clustering techniques have been proposed. Regrettably, the existing FCM technique does not generate accurate and standardized segmentation results. This is due to the noise present in the image as well as the random initialization of membership values for … …American Journal of Applied Sciences, Vol. 10, Issue 11 · 1 Oct 2013 · 6,819 accessesView PDFCite
Research ArticleOpen accessIn the abstractSMOOTHING SPLINE IN SEMIPARAMETRIC ADDITIVE REGRESSION MODEL WITH BAYESIAN APPROACHRita Diana, I. Nyoman Budiantara, Purhadi, Satwiko DarmestoSemiparametric additive regression model is a combination of parametric and nonparametric regression models. The parametric components are not linear but following a polynomial pattern, while the nonparametric components are unknown pattern and assumed to be contained in the Sobolev space. The nonparametric components can be approximated by smoothing spline functions. In the development of smoothing spline, the classical statistical approach … …Journal of Mathematics and Statistics, Vol. 9, Issue 3 · 12 Jun 2013 · 7,252 accessesView PDFCite
Research ArticleOpen accessIn the abstractBayesian Exploration of Multilocus Interactions on the Genome-Wide ScaleIvan Kozyryev, Jing ZhangProblem statement: Recent technological and scientific advances propelled the field of Genome-Wide Association Study (GWAS), which promises to be instrumental in linking many common complex diseases to their genetic origin. While so far such large-scale surveys have been moderately successful in identifying disease related genetic variants, much of disease heritability is still not accounted for by the discovered loci. There … …Current Research in Bioinformatics, Vol. 1, Issue 1 · 2 Jul 2012 · 7,401 accessesView PDFCite
Research ArticleOpen accessIn the abstractToward a Hierarchical Bayesian Framework for Modelling the Effect of Regional Diversity on Household ExpenditurePudji Ismartini, Nur Iriawan, Setiawan, Brodjol Sutijo Supri UlamaProblem statement: Household expenditure analysis was highly demanding for government in order to formulate its policy. Since household data was viewed as hierarchical structure with household nested in its regional residence which varies inter region, the contextual welfare analysis was needed. This study proposed to develop a hierarchical model for estimating household expenditure in an attempt to measure the effect … …Journal of Mathematics and Statistics, Vol. 8, Issue 2 · 25 Jun 2012 · 7,304 accessesView PDFCite
Research ArticleOpen accessIn the abstractBayesian Determination of Disease Associated Differences in Haplotype BlocksIvan Kozyryev, Jing ZhangProblem statement: While experimental ascertainment of haplotype blocks in the genome-scale case-control studies is expensive, accurate computational phasing is still a daunting task for bioinformatics approaches. We used a statistical method to determine differences, potentially associated with a certain disease, in linkage disequilibrium block boundaries in whole-genome Single Nucleotide Polymorphisms (SNPs) data. Approach: We utilized a Bayesian model for calculating … …Current Research in Bioinformatics, Vol. 1, Issue 1 · 14 Feb 2012 · 8,423 accessesView PDFCite