Discriminative Parameter Learning of General Bayesian Network Classifiers
- Bin Shen
- Xiaoyuan Su
- Russ Greiner, Dept of Computing Science; PI of AICML
- Petr Musilek
- Corrine Cheng
Greiner and Zhou [1] presented ELR, a discriminative parameter-learning algorithm that maximizes conditional likelihood (CL) for a fixed Bayesian Belief Network (BN) structure, and demonstrated that it often produces classifiers that are more accurate than the ones produced using the generative approach (OFE), which finds maximal likelihood parameters. This is especially true when learning parameters for incorrect structures, such as Na ve Bayes (NB). In searching for algorithms to learn better BN classifiers, this paper uses ELR to learn parameters of more nearly correct BN structures e.g., of a general Bayesian network (GBN) learned from a structure-learning algorithm [2]. While OFE typically produces more accurate classifiers with GBN (vs. NB), we show that ELR does not, when the training data is not sufficient for the GBN structure learner to produce a good model. Our empirical studies also suggest that the better the BN structure is, the less advantages ELR has over OFE, for classification purposes. ELR learning on NB (i.e., with little structural knowledge) still performs about the same as OFE on GBN in classification accuracy, over a large number of standard benchmark datasets.
The empirical data used in our experiments is here.
Citation
B. Shen, X. Su, R. Greiner, P. Musilek, C. Cheng. "Discriminative Parameter Learning of General Bayesian Network Classifiers". Fifteenth IEEE International Conference on Tools with Artificial Intelligence (ICTAI), Sacramento, California, November 2003.| Keywords: | discriminative, Parameter Learning, machine learning, belief nets, Bayesian Classifiers, probabilistic graphical models |
| Category: | In Conference |
BibTeX
@incollection{Shen+al:ICTAI03,
author = {Bin Shen and Xiaoyuan Su and Russ Greiner and Petr Musilek and
Corrine Cheng},
title = {Discriminative Parameter Learning of General Bayesian Network
Classifiers},
booktitle = {Fifteenth IEEE International Conference on Tools with Artificial
Intelligence (ICTAI)},
year = 2003,
}Last Updated: April 24, 2007Submitted by AICML Admin Assistant
