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A Consistency Result for Bayes Classifiers with Censored Response Data
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- Wijayatunga, Priyantha (author)
- Umeå universitet,Statistik
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- de Luna, Xavier (author)
- Umeå universitet,Statistik
- (creator_code:org_t)
- 2013
- 2013
- English.
- In: Theoretical mathematics and applications. - 1792-9709. ; 3:4, s. 47-54
- Journal article (peer-reviewed)
Abstract
Subject headings
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- Naive Bayes classifiers have proven to be useful in many prediction problems with complete training data. Here we consider the situation where a naive Bayes classifier is trained with data where the response is right censored. Such prediction problems are for instance encountered in profiling systems used at National Employment Agencies. In this paper we propose the maximum collective conditional likelihood estimator for the prediction and show that it is strongly consistent under the usual identifiability condition.
Subject headings
- NATURVETENSKAP -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Probability Theory and Statistics (hsv//eng)
Keyword
- Bayesian networks
- maximum collective conditional likelihood estimator
- strong consistency
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- ref (subject category)
- art (subject category)
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