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Analysis of evidence-theoretic decision rules for pattern classification

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1999Reasoning with imprecise belief structures176 cited
2019Logistic regression, neural networks and Dempster–Shafer theory: A new perspective152 cited
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2006Classification Using Belief Functions: Relationship Between Case-Based and Model-Based Approaches143 cited
2008Supplier selection in a fuzzy group setting: A method using grey related analysis and Dempster–Shafer theory142 cited
2001Handling possibilistic labels in pattern classification using evidential reasoning136 cited
2000Modeling vague beliefs using fuzzy-valued belief structures135 cited
2010Classifier fusion in the Dempster–Shafer framework using optimized t-norm based combination rules120 cited
2006On the combination and normalization of interval-valued belief structures☆113 cited
2021Partial classification in the belief function framework

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2016Dissimilarity Metric Learning in the Belief Function Framework41 cited

2010On the dynamic evidential reasoning algorithm for fault prediction39 cited

2007Building ensemble classifiers using belief functions and OWA operators37 cited