We provide an overview of problems related to variable selection (also known as feature selection) techniques in … currently used variable selection approaches, are addressed and illustrated on real-world examples. …

variable selection into a research topic of interest both in academia and in industry. The use of redundant, irrelevant, and … data collection. In this paper, we present a literature review on recent variable selection methods and applications in … manufacturing and in the chemometrics field. These methods are deployed into two major categories: variable selection for prediction …

with Y. Moreover when this variable selection rule is used for dimension reduction prior to applying classification … variable Xj is computed conditionally by using tubes to restrict the other variables. This variable selection procedure is …

variable selection methods based on entropy using 8 data sets from various domains as well as simulated data. The method is …

were based. In addition, the simulated datasets are used to compare variable selection strategies for confounder adjustment …

. In this paper, we propose a three-level variable selection approach based on weighed least squares with group SCAD …

variable selection. We demonstrate on simulated and real datasets that our approach is easily extendable to non …

We focus on the problem of simultaneous variable selection and estimation for nonlinear models based on modal …

variable selection procedure based on SCAD penalty is developed to select significant parametric covariates and is shown to …

In linear mixed models, the conditional Akaike Information Criterion (cAIC) is a procedure for variable selection in …