JNCC2: An extension of naive Bayes classifier suited for small and incomplete data sets
نویسندگان
چکیده
JNCC2 implements the Naive Credal Classifier 2 (NCC2), i.e., an extension of naive Bayes to imprecise probabilities, designed to return robust classification even on small and/or incomplete data sets, which is often the case in environmental case studies.
منابع مشابه
JNCC 2 user manual and tutorial ( rev 1 )
This paper introduces JNCC2, the Java implementation of the Naive Credal Classifier 2 (NCC2). JNCC2 is open source; it is hence freely available together with manual, sources and javadoc documentation. NCC2 is an extension of Naive Bayes Classifier (NBC) to imprecise probabilities, designed so as to return robust classifications even on small and/or incomplete data sets. A peculiar feature of N...
متن کاملJNCC2: the Java implementation of the Naive Credal Classifier2
This paper introduces JNCC2, the Java implementation of the Naive Credal Classifier2 (NCC2). JNCC2 is open source; it is hence freely available together with manual, sources and javadoc documentation. JNCC2 implements the Naive Credal Classifier2 (NCC2), i.e., an extension of Naive Bayes Classifier (NBC) towards imprecise probabilities. NCC2 is designed to return robust classification, even on ...
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This paper introduces JNCC2, the Java implementation of the Naive Credal Classifier2 (NCC2). JNCC2 is open source; it is hence freely available together with manual, sources and javadoc documentation. JNCC2 implements the Naive Credal Classifier2 (NCC2), i.e., an extension of Naive Bayes Classifier (NBC) towards imprecise probabilities. NCC2 is designed to return robust classification, even on ...
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Naive Credal Classifier, which is an imprecise-probability counterpart of Naive Bayes, is rigorously extended to a very general and flexible treatment of incomplete data, yielding a new classifier called Naive Credal Classifier 2 (NCC2). The new classifier delivers classifications that are robust to the presence of small sample sizes and missing values. In particular, some empirical evaluations...
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In this paper, the naive credal classifier, which is a set-valued counterpart of naive Bayes, is extended to a general and flexible treatment of incomplete data, yielding a new classifier called naive credal classifier 2 (NCC2). The new classifier delivers classifications that are reliable even in the presence of small sample sizes and missing values. Extensive empirical evaluations show that, ...
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عنوان ژورنال:
- Environmental Modelling and Software
دوره 23 شماره
صفحات -
تاریخ انتشار 2008