Structural Extension to Logistic Regression Discriminative Parameter Learning of Belief Net Classifiers.
Bayesian belief nets (BNs) are often used for classification tasks-typically to return the most likely class label for each specified instance. Many BN-learners, however, attempt to find the BN that maximizes a different objective function-viz., likelihood, rathen than classification accuracy-typica...
| Pubblicato in: | Machine learning. 59, 3 (2005). |
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| Natura: | Articolo |
| Lingua: | English |
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