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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发表在:	Machine learning. 59, 3 (2005).
主要作者:	Greiner, Russell
格式:	文件
语言:	English
主题:	(Bayesian) belief nets. Logistic regression. Classification. PAC-learning. Computational/sample complexity.