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9 articles for “Bayesian Network Learning”
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Research ArticleOpen accessEvery word in the titleMCMC-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 accessEvery word in the titleFuzzy Method for Online Learning of Bayesian Network ParametersMariana D.C. Lima, Silvia M. NassarIn learning problems, there are situations where training data is not fully available at the learning time. They are incrementally generated by time, defining a type of domain called online that has among its characteristics the possibility of data failure or even missing data. In Bayesian networks, learning is divided into two categories: structure (related to the graph of conditional … …Journal of Computer Science, Vol. 15, Issue 3 · 16 Mar 2019 · 7,498 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA 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 abstractDevelopment of Big Data Classifier for Biomedicine Early Diagnosis: An Experimental Approach Using Machine Learning MethodsMa Beth Solas Concepcion, Bobby Dioquino Gerardo, Frank Ibañez Elijorde et al.In the fast-phase world, data availability is abundant due to a rapid adaptation increase of big data technologies. Large amounts of data have been generated and collected at an unprecedented speed and scale, introducing a revolution in medical research practices for biomedicine informatics. Thus, there is an immense demand for statistically rigorous approaches, especially in the medical diagnosis discipline. Therefore, … …Journal of Computer Science, Vol. 20, Issue 4 · 1 Feb 2024 · 5,510 accessesView PDFCite
Research ArticleOpen accessIn the abstractCascade-Based Non-Linear Feedforward Neural Networks for Bi-Directional MemoryThipendra Pal Singh, Tanupriya Choudhury, Rohini AIn today's world, efficient computation is the key to success in many fields. Pattern association plays an influential role in many areas of life, such as learning and memory. In complex dynamics, bidirectional associative memory has been effectively demonstrated by neural networks. However, these neural networks face challenges in terms of performance, such as computational time. A random bipolar input … …Journal of Computer Science, Vol. 19, Issue 4 · 28 Feb 2023 · 5,640 accessesView PDFCite
Research ArticleOpen accessIn the abstractKnowledge Based Bayesian Network Construction Algorithm for Medical Data Fusion to Enhance Services and DiagnosisAhmed SamehTraditional Bayesian networks' algorithms are treating the network construction process as an isolated and autonomous data-driven trial-and-error process and completely ignoring the domain knowledge. In this work we are proposing a new 'Semantically Aware Ontology-Based Bayesian Network construction algorithm' that is knowledge centered instead of data centered. The objective of the new algorithm is to empower patients through improving their … …Journal of Computer Science, Vol. 15, Issue 5 · 28 May 2019 · 8,035 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 abstractDiagnosis of Cardiovascular Diseases with Bayesian ClassifiersAlaa Elsayad, Mahmoud FakhrCardiovascular disease or atherosclerosis is any disease affecting the cardiovascular system. They include coronary heart disease, raised blood pressure, cerebrovascular disease, peripheral artery disease, rheumatic heart disease, congenital heart disease and heart failure. They are treated by cardiologists, thoracic surgeons, vascular surgeons, neurologists and interventional radiologists. The diagnosis is an important yet complicated task that needs to be done accurately … …Journal of Computer Science, Vol. 11, Issue 2 · 25 Mar 2015 · 7,498 accessesView PDFCite