A Consistency Result for Bayes Classifiers with Censored Response Data
2013 (English)In: Theoretical mathematics and applications, ISSN 1792-9709, Vol. 3, no 4, 47-54 p.Article in journal (Refereed) Published
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.
Place, publisher, year, edition, pages
2013. Vol. 3, no 4, 47-54 p.
Bayesian networks, maximum collective conditional likelihood estimator, strong consistency
Probability Theory and Statistics
IdentifiersURN: urn:nbn:se:umu:diva-85225OAI: oai:DiVA.org:umu-85225DiVA: diva2:692266