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
Research ArticleOpen accessIn the abstractHEURISTIC DISCRETIZATION METHOD FOR BAYESIAN NETWORKSMariana D.C. Lima, Silvia M. Nassar, Pedro Ivo R.B.G. Rodrigues et al.Bayesian Network (BN) is a classification technique widely used in Artificial Intelligence. Its structure is a Direct Acyclic Graph (DAG) used to model the association of categorical variables. However, in cases where the variables are numerical, a previous discretization is necessary. Discretization methods are usually based on a statistical approach using the data distribution, such as division by quartiles. In … …Journal of Computer Science, Vol. 10, Issue 5 · 18 Jan 2014 · 7,054 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 abstractANALYSIS 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 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
Research ArticleOpen accessIn the abstractAdaptive Channel Equalization Using Multiplicative Neural Network for Rayleigh Faded ChannelP. Sivakumar, N. Chithra, S. N. Sivanandam, M. RajaramProblem statement: Digital transmission over band-limited communication channel largely suffers from ISIS and various noise sources. The presence of ISI and noise causes bit errors in the received signal. Equalization is necessary at the receiver to overcome these channel impairment to recover the original transmitted sequence. Traditionally equalization is considered as equivalent to inverse filtering and implemented using linear-perform under … …Journal of Computer Science, Vol. 7, Issue 11 · 18 Aug 2011 · 6,931 accessesView PDFCite
Research ArticleOpen accessIn the abstractStatistical Bayesian Learning for Automatic Arabic Text CategorizationBassam Al-Salemi, Mohd. Juzaiddin Ab AzizProblem statement: The rapid increasing of online Arabic documents necessitated applying Text Categorization techniques that are commonly used for English language to categorize them automatically. The complex morphology of Arabic language and its large vocabulary size make applying these techniques directly difficult and costly in time and effort. Approach: We have investigated Bayesian learning models in order to enhance Arabic … …Journal of Computer Science, Vol. 7, Issue 1 · 27 Dec 2010 · 8,399 accessesView PDFCite