Bayesian confirmation measures within rough set approach

Bayesian confirmation theory considers a variety of non-equivalent confirmation measures quantifying the degree to which a piece of evidence supports a hypothesis. In this paper, we apply some of the most relevant confirmation measures within the rough set approach, Moreover, we discuss interesting properties of these confirmation measures and we propose a new property of monotonicity that is particularly relevant within rough set approach. The main result of this paper states which one of the confirmation measures considered in the literature have the desirable properties from the viewpoint of the rough set approach.



Titolo: Bayesian confirmation measures within rough set approach
Autori interni: 
GRECO, Salvatore (Corresponding)
mostra contributor esterni 
Data di pubblicazione: 2004
Serie: 
LECTURE NOTES IN ARTIFICIAL INTELLIGENCE  
Handle: http://hdl.handle.net/20.500.11769/361678
Appare nelle tipologie:2.1 Contributo in volume (Capitolo o Saggio)

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http://hdl.handle.net/20.500.11769/361678
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