Titlebook: Computational Discovery of Scientific Knowledge; Introduction, Techni Sašo Džeroski,Ljupčo Todorovski Book 2007 Springer-Verlag Berlin Heid

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Discovering Communicable Models from Earth Science Data application of machine learning, it is crucially important for the learned models to be . and .. We recount how we selected a learning algorithm to maximize communicability, and then describe two visualization techniques that we developed to aid in understanding the model by exploiting the spatial

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Computational Discovery in Pure Mathematicsystems, automated theorem provers, programs designed to generate examples, mathematical databases, and theory formation programs on the body of knowledge in pure mathematics. We discuss to what extent the output from certain programs can be considered a discovery in pure mathematics. This enables us

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Automatic Computational Discovery of Chemical Reaction Networks Using Genetic Programmings. Recent work has demonstrated that genetic programming is capable of automatically creating complex networks (such as analog electrical circuits and controllers) whose behavior is modeled by linear and non-linear continuous-time differential equations and whose behavior matches prespecified output

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Logic and the Automatic Acquisition of Scientific Knowledge: An Application to Functional Genomicsexperiencing an unprecedented “explosion” in the amount of available data; traditional data analysis methods cannot deal with this increased quantity of data; there is an urgent need to automate the process of refining scientific data into scientific knowledge; inductive logic programming (ILP) is a

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