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12 results for “Bayesian classifier”
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Research ArticleOpen accessPhrase in the titleDiagnosis 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
Research ArticleOpen accessPhrase in the titleFrom Feature Selection to Building of Bayesian Classifiers: A Network Intrusion Detection PerspectiveKok-Chin Khor, Choo-Yee Ting, Somnuk-Phon AmnuaisukProblem statement: Implementing a single or multiple classifiers that involve a Bayesian Network (BN) is a rising research interest in network intrusion detection domain. Approach: However, little attention has been given to evaluate the performance of BN classifiers before they could be implemented in a real system. In this research, we proposed a novel approach to select important features by … …American Journal of Applied Sciences, Vol. 6, Issue 11 · 30 Nov 2009 · 7,072 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleANALYSIS OF BAYESIAN CLASSIFIER ACCURACYFelipe Schneider Costa, Maria Marlene De Souza Pires, Silvia Modesto NassarThe naïve Bayes classifier is considered one of the most effective classification algorithms today, competing with more modern and sophisticated classifiers. Despite being based on unrealistic (naïve) assumption that all variables are independent, given the output class, the classifier provides proper results. However, depending on the scenario utilized (network structure, number of samples or training cases, number of variables), the … …Journal of Computer Science, Vol. 9, Issue 11 · 26 Sep 2013 · 8,375 accessesView PDFCite
Research ArticleOpen accessPhrase in the titlePredicting the Severity of Breast Masses with Ensemble of Bayesian ClassifiersAlaa M. ElsayadProblem statement: This study evaluated two different Bayesian classifiers; tree augmented Naive Bayes and Markov blanket estimation networks in order to build an ensemble model for prediction the severity of breast masses. The objective of the proposed algorithm was to help physicians in their decisions to perform a breast biopsy on a suspicious lesion seen in a mammogram image or … …Journal of Computer Science, Vol. 6, Issue 5 · 31 May 2010 · 7,299 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Drug-Target Interaction Prediction Based on Supervised Probabilistic ClassificationManmohan Singh, Susheel Kumar Tiwari, G. Swapna et al.Bayesian ranking-based drug-target relationship prediction has achieved good results, but it ignores the relationship between drugs of the same target. A new method is proposed for drug-target relationship prediction based on groups by Appling Bayesian. According to the reality that drugs interacting with a specific target have similarities, a grouping strategy was introduced to make these similar drugs interact. A … …Journal of Computer Science, Vol. 19, Issue 10 · 1 Sep 2023 · 5,454 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Gene Selection Algorithm using Bayesian Classification ApproachAlok Sharma, Kuldip K. PaliwalIn this study, we propose a new feature (or gene) selection algorithm using Bayes classification approach. The algorithm can find gene subset crucial for cancer classification problem. Problem statement: Gene identification plays important role in human cancer classification problem. Several feature selection algorithms have been proposed for analyzing and understanding influential genes using gene expression profiles. Approach: The feature selection … …American Journal of Applied Sciences, Vol. 9, Issue 1 · 24 Nov 2011 · 8,307 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 abstractA NOVEL EMAIL RESPONSE ALGORITHM FOR EMAIL MANAGEMENT SYSTEMSAbdulkareem Al-AlwaniEmail has been one of the most commonly used tool for communication in the recent years and email management has evolved as a major challenge due to prevailing situation of online email congestion. This study presents a novel algorithm for automatic email response methodology in an Email Management System to minimize email overload. The proposed model uses Bayes classifier to … …Journal of Computer Science, Vol. 10, Issue 4 · 23 Dec 2013 · 7,049 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 abstractA Hidden Genetic Layer Based Neural Network for Mobility PredictionL. Velmurugan, P. ThangarajProblem statement: With numerous wireless devices increasingly connecting to the internet, WLAN infrastructure planning becomes very important to maintain desired quality of services. For maintaining desired quality of service it is desirable to know the movement pattern of users. Mobility prediction involves finding the mobile device's next access point as it moves through the wireless network. Hidden Markov models and … …American Journal of Applied Sciences, Vol. 9, Issue 4 · 11 Feb 2012 · 7,224 accessesView PDFCite