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Naive Bayes classifier

Known as: Bayesian Classifiers, Naive-Bayes, Naïve Bayesian classification 
In machine learning, naive Bayes classifiers are a family of simple probabilistic classifiers based on applying Bayes' theorem with strong (naive… 
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Papers overview

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2013
2013
Probability estimation from a given set of training examples is crucial for learning Naive Bayes (NB) Classifiers. For an… 
2012
2012
Intrusion detection is the process of monitoring and analyzing the events occurring in a computer system in order to detect signs… 
2009
2009
Curently, internet content growth rapidly. Automatic news classification is the classification of news into a category. In this… 
2007
2007
Naive-Bayes classifier is a popular technique of classification in machine learning. Improving the accuracy of naive-Bayes… 
Highly Cited
2007
Highly Cited
2007
In this paper, we propose a hardware implementation of the EMS decoding algorithm for non-binary LDPC codes, presented in [10… 
2006
2006
We propose a hardware architecture for a naive Bayes classifier in the context of e-mail classification for spam control. Our… 
Highly Cited
2004
Highly Cited
2004
  • R. Bouckaert
  • 2004
  • Corpus ID: 37154569
There are three main methods for handling continuous variables in naive Bayes classifiers, namely, the normal method (parametric… 
Highly Cited
2001
Highly Cited
2001
Sol−gel nanocasting is used to imprint the soft-matter structures of lyotropic phases of nonionic n-alkyl−poly(ethylene oxide… 
Highly Cited
2001
Highly Cited
2001
We develop the optimal Bayes multiframe detector/tracker for rigid extended targets that move randomly in clutter. The… 
Highly Cited
1999
Highly Cited
1999
Low dielectric constant, porous silica was made from commercially available methyl silsesquioxane (MSQ) by the addition of a…