A Distance-Based Decision in the Credal Level

January 28, 2015 Β· Declared Dead Β· πŸ› Artificial Intelligence and Symbolic Computation

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Authors Amira Essaid, Arnaud Martin, GrΓ©gory Smits, Boutheina Ben Yaghlane arXiv ID 1501.07008 Category cs.AI: Artificial Intelligence Citations 18 Venue Artificial Intelligence and Symbolic Computation Last Checked 4 months ago
Abstract
Belief function theory provides a flexible way to combine information provided by different sources. This combination is usually followed by a decision making which can be handled by a range of decision rules. Some rules help to choose the most likely hypothesis. Others allow that a decision is made on a set of hypotheses. In [6], we proposed a decision rule based on a distance measure. First, in this paper, we aim to demonstrate that our proposed decision rule is a particular case of the rule proposed in [4]. Second, we give experiments showing that our rule is able to decide on a set of hypotheses. Some experiments are handled on a set of mass functions generated randomly, others on real databases.
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