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132

EUSFLAT
2003

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Bayesian networks for continuous values and uncertainty in the learning process

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Bayesian networks for continuous values and uncertainty in the learning process

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This paper proposes a method for Bayesian networks that handles uncertainty and discretization of continuous variables when learning the networks from a database of cases. The database is reorganised in a new form of representation called reduced database where data are treated as distributions on symbolic values.

J. F. Baldwin, E. Di Tomaso

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Added	31 Oct 2010
Updated	31 Oct 2010
Type	Conference
Year	2003
Where	EUSFLAT
Authors	J. F. Baldwin, E. Di Tomaso

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