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Learning accurate and concise naïve Bayes classifiers from attribute value taxonomies and data
In many application domains, there is a need for learning algorithms that can effectively exploit attribute value taxonomies (AVT)—hierarchical groupings of attribute values—to learn compact, comprehensible and accurate classifiers from data—including data that are partially specified. This paper de...
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| Main Authors: | , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2006
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2846370/ https://ncbi.nlm.nih.gov/pubmed/20351793 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s10115-005-0211-z |
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