Using distance covariance for improved variable selection with application to learning genetic risk models
Using distance covariance for improved variable selection with application to learning genetic risk models
Variable selection is of increasing importance to address the difficulties of high dimensionality in many scientific areas. In this paper, we demonstrate a property for distance covariance, which is incorporated in a novel feature screening procedure together with the use of distance correlation. The approach makes no distributional assumptions for …