In streamwise feature selection, new features are sequentially considered for addition to a predictive model. When the space of potential features is large, streamwise feature sel...
Jing Zhou, Dean P. Foster, Robert A. Stine, Lyle H...
Feature selection for supervised learning can be greatly improved by making use of the fact that features often come in classes. For example, in gene expression data, the genes wh...
Paramveer S. Dhillon, Dean P. Foster, Lyle H. Unga...
The visualization of any vector field is dependent on the relative velocity of the observer. In experimentally generated vector fields, the average value of the streamwise compone...
Timothy Urness, Victoria Interrante, Ellen Longmir...
—Stability (robustness) of feature selection methods is a topic of recent interest, yet often neglected importance, with direct impact on the reliability of machine learning syst...