We consider regression experiments involving a response varible Y and a large number of predictor variables X1,...,Xd, many of which may be irrelevant for the prediction of Y and thus must be removed ...

Instance selection plays a pivotal role in enhancing machine learning by identifying and retaining those data instances that are most informative for the learning process, while discarding redundant ...

Variable selection is fundamental to high-dimensional statistical modeling. Many variable selection techniques may be implemented by maximum penalized likelihood using various penalty functions.

The DHR architecture breaks the pattern of staticity, similarity, and determinism of cyberspace security information systems through multiple heterogeneities in different spatial-temporal dimensions.