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… (More)
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2009
2009
A Bayesian Network (BN) takes a relationship between graphs and probability distributions. In the past, BN was mainly used for… (More)
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Highly Cited
2009
Highly Cited
2009
Privacy enhancing technologies like OpenSSL, OpenVPN or Tor establish an encrypted tunnel that enables users to hide content and… (More)
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Highly Cited
2007
Highly Cited
2007
A basic assumption in traditional machine learning is that the training and test data distributions should be identical. This… (More)
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Highly Cited
2004
Highly Cited
2004
Privacy-Preserving Data Mining – developing models without seeing the data – is receiving growing attention. This paper assumes a… (More)
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Highly Cited
2004
Highly Cited
2004
We augment naive Bayes models with statistical n-gram language models to address short-comings of the standard naive Bayes text… (More)
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Highly Cited
2003
Highly Cited
2003
The problem of secure distributed classification is an important one. In many situations, data is split between multi ple… (More)
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2003
2003
The Naive Bayes classifier is a simple and accurate classifier. This paper shows that assuming the Naive Bayes classifier model… (More)
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Highly Cited
2002
Highly Cited
2002
Recognizing human facial expression and emotion by computer is an interesting and challenging problem. In this paper we propose a… (More)
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Highly Cited
2001
Highly Cited
2001
We compare discriminative and generative learning as typified by logistic regression and naive Bayes. We show, contrary to a… (More)
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Highly Cited
1998
Highly Cited
1998
Recent approaches to text classification have used two different first-order probabilistic models for classification, both of… (More)
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