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» Non-Disjoint Discretization for Naive-Bayes Classifiers
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ICML
2002
IEEE
14 years 5 months ago
Non-Disjoint Discretization for Naive-Bayes Classifiers
Previous discretization techniques have discretized numeric attributes into disjoint intervals. We argue that this is neither necessary nor appropriate for naive-Bayes classifiers...
Ying Yang, Geoffrey I. Webb
AUSAI
2003
Springer
13 years 8 months ago
On Why Discretization Works for Naive-Bayes Classifiers
We investigate why discretization is effective in naive-Bayes learning. We prove a theorem that identifies particular conditions under which discretization will result in naiveBay...
Ying Yang, Geoffrey I. Webb
FSKD
2006
Springer
115views Fuzzy Logic» more  FSKD 2006»
13 years 8 months ago
Improvement of Decision Accuracy Using Discretization of Continuous Attributes
Abstract. The na
Qingxiang Wu, David A. Bell, T. Martin McGinnity, ...
CORR
2002
Springer
132views Education» more  CORR 2002»
13 years 4 months ago
Robust Feature Selection by Mutual Information Distributions
Mutual information is widely used in artificial intelligence, in a descriptive way, to measure the stochastic dependence of discrete random variables. In order to address question...
Marco Zaffalon, Marcus Hutter
PAMI
2007
107views more  PAMI 2007»
13 years 4 months ago
Recognition of Pornographic Web Pages by Classifying Texts and Images
—With the rapid development of the World Wide Web, people benefit more and more from the sharing of information. However, Web pages with obscene, harmful, or illegal content can ...
Weiming Hu, Ou Wu, Zhouyao Chen, Zhouyu Fu, Stephe...