Possibilistic conditional independence: A similarity-based measure and its application to causal network learning

DOI10.1016/S0888-613X(98)00012-7zbMath0941.68120MaRDI QIDQ1818003

Joan Cabós, Ulises Cortés, Ramón Sangüesa

Publication date: 27 January 2000

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

zbMATH Keywords

similarityhybrid algorithm

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Theory of languages and software systems (knowledge-based systems, expert systems, etc.) for artificial intelligence (68T35)

Related Items (2)

Evaluating Product-Based Possibilistic Networks Learning Algorithms ⋮ SIM-PDT: A Similarity Based Possibilistic Decision Tree Approach

Uses Software

• UCI-ml

Cites Work

• Axioms of causal relevance
• A Bayesian method for the induction of probabilistic networks from data
• Fuzzy sets as a basis for a theory of possibility
• Conditional possibilities independence and noninteraction
• The context model: An integrating view of vagueness and uncertainty
• Construction of Bayesian network structures from data: A brief survey and an efficient algorithm
• An axiomatic framework for propagating uncertainty in directed acyclic networks
• Belief networks revisited
• Approximating discrete probability distributions with dependence trees
• Upper and Lower Probabilities Induced by a Multivalued Mapping
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