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In this paper we consider the application of machine learning of graphical models and feature selection for developing better drug-design strategies. The work discussed in this paper is based on utilizing partial prior knowledge available through KEGG signalling pathway database in tan dim with our recent developed ensemble feature selection methods for a better regularisation of the lasso estimate...
Wind turbine operation and maintenance costs depend on the reliability of its components. Thus, a critical task is to detect and isolate faults, as fast as possible, and restore optimal operating conditions in the shortest time. In this paper, a machine learning of graphical models approach is proposed for fault diagnosis of wind turbines, in particular pitch system. The role of the latter is to adjust...
Bayesian network structures are usually built using only the data and starting from an empty network or from a naive Bayes structure. Very often, in some domains, like medicine, a prior structure is already known based on expert knowledge. This structure can be automatically or manually refined in search for better performance models. In this work, we take Bayesian networks built by specialists and...
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