-tness function, thereby treating model selection as an optimisation problem. However, it is unrealistic to believe that the -ttest model represents the best solution to the search problem. In fact, even if it is possible to score all of the candidate models, it hardly happens that there exists an unequivocal answer to the question of which model best explains data. An automatic model search procedure for the identi-cation of an optimal set of good models is proposed. In a technological approach to model selection the identi-ed models can co-exist, whereas in a scienti-c modelling approach such models represent a starting point for further context-dependent analysis. An example of the application of the proposed procedure to real data is given.

Technological modelling for graphical models: an approach basedon genetic algorithms

ROVERATO, ALBERTO;
2004

Abstract

-tness function, thereby treating model selection as an optimisation problem. However, it is unrealistic to believe that the -ttest model represents the best solution to the search problem. In fact, even if it is possible to score all of the candidate models, it hardly happens that there exists an unequivocal answer to the question of which model best explains data. An automatic model search procedure for the identi-cation of an optimal set of good models is proposed. In a technological approach to model selection the identi-ed models can co-exist, whereas in a scienti-c modelling approach such models represent a starting point for further context-dependent analysis. An example of the application of the proposed procedure to real data is given.
2004
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3280893
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