Nature

Variable selection for inferential models with relatively high-dimensional data: Between method heterogeneity and covariate stability as adjuncts to robust selection

Variable selection in inferential modelling is problematic when the number of variables is large relative to the number of data points, especially when multicollinearity is present. A variety of ...
Nature

Variable selection with false discovery rate control in deep neural networks

Deep neural networks (DNNs) are a popular machine-learning technique and have shown superior performance in many scientific problems. Despite their high prediction accuracy, DNNs are often criticized ...