-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 gi...
An important problem in economics and other areas of science is finding the mathematical relationshi...
Udgivelsesdato: NOVThis paper introduces graphical models as a natural environment in which to formu...
Model learning often implies exploring a vast search space of possible hypotheses in the hope of fin...
-tness function, thereby treating model selection as an optimisation problem. However, it is unreal...
Automatic model search procedures aim at identifying the model that maximises a given fitness functi...
Model selection is ubiquitous as we simply do not know the underlying data generating process. Howev...
AIC, Genetic Algorithm, Graphical model, Log-linear model, Model selection, Undirected graph,
Abstract. A real-world system has often plenty of variables that affect its behaviour. To be able to...
The properties of automatic model selection are discussed, focusing on PcGets. We explain the backgr...
In this paper, we describe some evolutionaryapproaches based on genetic algorithms to face the stati...
In the era of big data, analysts usually explore various statistical models or machine-learning meth...
In this paper, we present a graphical method for selection of the model among the many competitive m...
Typically, economists develop models by first selecting a model structure based on theoretical consi...
People from a variety of industrial domains are beginning to realise that appropriate use of machine...
The expressive power, powerful search capability, and the explicit nature of the resulting models ma...
An important problem in economics and other areas of science is finding the mathematical relationshi...
Udgivelsesdato: NOVThis paper introduces graphical models as a natural environment in which to formu...
Model learning often implies exploring a vast search space of possible hypotheses in the hope of fin...
-tness function, thereby treating model selection as an optimisation problem. However, it is unreal...
Automatic model search procedures aim at identifying the model that maximises a given fitness functi...
Model selection is ubiquitous as we simply do not know the underlying data generating process. Howev...
AIC, Genetic Algorithm, Graphical model, Log-linear model, Model selection, Undirected graph,
Abstract. A real-world system has often plenty of variables that affect its behaviour. To be able to...
The properties of automatic model selection are discussed, focusing on PcGets. We explain the backgr...
In this paper, we describe some evolutionaryapproaches based on genetic algorithms to face the stati...
In the era of big data, analysts usually explore various statistical models or machine-learning meth...
In this paper, we present a graphical method for selection of the model among the many competitive m...
Typically, economists develop models by first selecting a model structure based on theoretical consi...
People from a variety of industrial domains are beginning to realise that appropriate use of machine...
The expressive power, powerful search capability, and the explicit nature of the resulting models ma...
An important problem in economics and other areas of science is finding the mathematical relationshi...
Udgivelsesdato: NOVThis paper introduces graphical models as a natural environment in which to formu...
Model learning often implies exploring a vast search space of possible hypotheses in the hope of fin...