Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Machine Learning - Special issue on learning with probabilistic representations
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Eighteenth national conference on Artificial intelligence
Learning Bayesian network classifiers by maximizing conditional likelihood
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Representing conditional independence using decision trees
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
Classifying Biomedical Abstracts Using Committees of Classifiers and Collective Ranking Techniques
Canadian AI '09 Proceedings of the 22nd Canadian Conference on Artificial Intelligence: Advances in Artificial Intelligence
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
e-mail authorship verification for forensic investigation
Proceedings of the 2010 ACM Symposium on Applied Computing
Advances in Human-Computer Interaction - Special issue on emotion-aware natural interaction
ADMI'10 Proceedings of the 6th international conference on Agents and data mining interaction
A comparison of machine learning techniques for detection of drug target articles
Journal of Biomedical Informatics
Discriminative Learning of Bayesian Networks via Factorized Conditional Log-Likelihood
The Journal of Machine Learning Research
Improving Tree augmented Naive Bayes for class probability estimation
Knowledge-Based Systems
Mining photo-sharing websites to study ecological phenomena
Proceedings of the 21st international conference on World Wide Web
Speaker recognition from encrypted VoIP communications
Digital Investigation: The International Journal of Digital Forensics & Incident Response
Network intrusion detection system: a machine learning approach
Intelligent Decision Technologies
Evaluation of normalization techniques in text classification for portuguese
ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part III
Abstracting for Dimensionality Reduction in Text Classification
International Journal of Intelligent Systems
Learning attentive fusion of multiple bayesian network classifiers
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part III
Bandit-based structure learning for bayesian network classifiers
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part II
An Augmented Value Difference Measure
Pattern Recognition Letters
Hi-index | 0.00 |
Bayesian network classifiers have been widely used for classification problems. Given a fixed Bayesian network structure, parameters learning can take two different approaches: generative and discriminative learning. While generative parameter learning is more efficient, discriminative parameter learning is more effective. In this paper, we propose a simple, efficient, and effective discriminative parameter learning method, called Discriminative Frequency Estimate (DFE), which learns parameters by discriminatively computing frequencies from data. Empirical studies show that the DFE algorithm integrates the advantages of both generative and discriminative learning: it performs as well as the state-of-the-art discriminative parameter learning method ELR in accuracy, but is significantly more efficient.