A belief function classifier based on information provided by noisy and dependent features

DOI10.1016/j.ijar.2009.11.008zbMath1217.68215OpenAlexW2085857591MaRDI QIDQ553969

Paul-André Monney, Moses Chan, Paul Romberg

Publication date: 29 July 2011

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

Full work available at URL: https://doi.org/10.1016/j.ijar.2009.11.008

zbMATH Keywords

Dempster-Shafer theorynoisy measurementsevidence theorydependent featuresobject classification

Mathematics Subject Classification ID

Reasoning under uncertainty in the context of artificial intelligence (68T37)

Related Items

The conjunctive combination of interval-valued belief structures from dependent sources, Confidence distributions: a review

Uses Software

• ABEL

Cites Work

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