The relabelling procedure is usually used to identify suspect samples with the intention to remove or relabel them into a concurrent, more appropriate class ...
Cautious classification aims to minimize errors by providing a reliable output based on an appropriate representation of uncertainty. The idea of favouring the ...
We therefore propose a relabelling procedure which allows us to identify imperfect samples in the training data and relabel them with an appropriate subset of ...
We therefore propose a relabelling procedure which allows us to identify imperfect samples in the training data and relabel them with an appropriate subset of ...
We therefore propose a relabelling procedure which allows us to identify imperfect samples in the training data and relabel them with an appropriate subset of ...
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What is the theory of belief functions?
May 15, 2020 · In this paper, we consider such an issue where the classifier provides imprecise and/or uncertain predictions that need to be managed within the decision ...
In real situations, we may have only partial knowledge of class labels: we have uncertainty in the data → partially supervised learning.
Missing: relabelling. | Show results with:relabelling.
) Because of the insights it promises conceming the relationship between probabilities and evidence, the theory of belief functions deserves careful attention.
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2022: Cautious classification based on belief functions theory and imprecise relabelling International Journal of Approximate Reasoning 142: 130-146 ...
... Imprecise Relabelling ... classification method using belief functions. ... Handling Mixture Optimisation Problem Using Cautious Predictions and Belief Functions.