Binary naive possibilistic classifiers: Handling uncertain inputs

DOI10.1002/int.20381zbMath1192.68667OpenAlexW4241581448MaRDI QIDQ3650905

Salem Benferhat, Karim Tabia

Publication date: 7 December 2009

Published in: International Journal of Intelligent Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/int.20381

zbMATH Keywords

possibilistic networks

Mathematics Subject Classification ID

Pattern recognition, speech recognition (68T10) Knowledge representation (68T30)

Related Items (1)

Inference in possibilistic network classifiers under uncertain observations

Cites Work

• Updating beliefs with incomplete observations
• Hybrid possibilistic networks
• Naïve possibilistic network classifiers
• Fuzzy sets as a basis for a theory of possibility
• Conditional possibilities independence and noninteraction
• Independence and possibilistic conditioning
• A synthetic view of belief revision with uncertain inputs in the framework of possibility theory
• A comparative study of possibilistic conditional independence and lack of interaction
• Modeling and Reasoning with Bayesian Networks
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Binary naive possibilistic classifiers: Handling uncertain inputs