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ARTMED
2004

Latent variable discovery in classification models

9 years 2 months ago
Latent variable discovery in classification models
The naive Bayes model makes the often unrealistic assumption that the feature variables are mutually independent given the class variable. We interpret a violation of this assumption as an indication of the presence of latent variables, and we show how latent variables can be detected. Latent variable discovery is interesting, especially for medical applications, because it can lead to a better understanding of application domains. It can also improve classification accuracy and boost user confidence in classification models.
Nevin Lianwen Zhang, Thomas D. Nielsen, Finn Verne
Added 16 Dec 2010
Updated 16 Dec 2010
Type Journal
Year 2004
Where ARTMED
Authors Nevin Lianwen Zhang, Thomas D. Nielsen, Finn Verner Jensen
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