Learning Bayesian network parameters from small data sets: Application of Noisy-OR gates

DOI10.1016/S0888-613X(01)00039-1zbMath0988.68827OpenAlexW2072063551MaRDI QIDQ5944735

Hanna Wasyluk, Agnieszka Oniśko, Marek J. Druzdzel

Publication date: 18 February 2002

Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0888-613x(01)00039-1

zbMATH Keywords

Bayesian networksHEPAR II

Mathematics Subject Classification ID

Computing methodologies and applications (68U99) Theory of languages and software systems (knowledge-based systems, expert systems, etc.) for artificial intelligence (68T35)

Related Items (11)

An Empirical Study of the Use of the Noisy-Or Model in a Real-Life Bayesian Network ⋮ Learning management knowledge for manufacturing systems in the early stages using time series data ⋮ Disjunctive interaction in continuous time Bayesian networks ⋮ Propagation effects of model-calculated probability values in Bayesian networks ⋮ An intercausal cancellation model for Bayesian-network engineering ⋮ Structural learning of mixed noisy-or Bayesian networks ⋮ Using virtual sample generation to build up management knowledge in the early manufacturing stages ⋮ A Bayesian network interpretation of the Cox's proportional hazard model ⋮ Using the Noisy-OR Model Can Be Harmful … But It Often Is Not ⋮ A new heuristic for learning Bayesian networks from limited datasets: a real-time recommendation system application with RFID systems in grocery stores ⋮ The extended recursive noisy or model: static and dynamic considerations

Uses Software

• TETRAD

Cites Work

• Causation, prediction, and search
• A Bayesian method for the induction of probabilistic networks from data
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