Classification with Hybrid Generative/Discriminative Models

Raina, Rajat, Shen, Yirong, McCallum, Andrew, Ng, Andrew Y.

Dec-31-2004–Neural Information Processing Systems

Classifiers often achieve higher test set accuracy than generative Classifiers (e.g., [6, 4, 14]).

algorithm, artificial intelligence, bayesian inference, (17 more...)

Neural Information Processing Systems

Dec-31-2004

Conferences PDF

Country:
- North America > United States
  - California > Santa Clara County (0.14)
  - Massachusetts (0.14)

Genre:
- Research Report > New Finding (0.96)

Technology:
- Information Technology > Artificial Intelligence
  - Machine Learning
    - Learning Graphical Models > Directed Networks
      - Bayesian Learning (1.00)
    - Statistical Learning (1.00)
  - Natural Language (1.00)
  - Representation & Reasoning > Uncertainty
    - Bayesian Inference (0.69)

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Classification with Hybrid Generative/Discriminative Models
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