Structural Extension to Logistic Regression Discriminative Parameter Learning of Belief Net Classifiers.

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...

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Bibliographic Details
Published in:Machine learning. 59, 3 (2005).
Main Author: Greiner, Russell
Format: Article
Language:English
Subjects:
(Bayesian) belief nets.
Logistic regression.
Classification.
PAC-learning.
Computational/sample complexity.