Abstract: Multioutput regression, referring to simultaneously predicting multiple continuous output variables with a single model, has drawn increasing attention in the machine learning community due ...
Background The link between drinking water salinity and increased blood pressure and hypertension risk among coastal and ...
Multiple regression analyses often assume that the response and covariates of each individual are observed, and use them to infer the regression coefficients. Here, motivated by the applications in ...
Abstract: The purpose of this study was to investigate the relationship between workload and in-game technical and athletic performance. To achieve this,A modeling approach that predicts multiple ...
Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...
What is a Gaussian Graphical Model ? A Gaussian graphical model captures conditional (in)dependencies among a set of variables. These are pairwise relations (partial correlations) controlling for the ...
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