Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1151666 | Statistics & Probability Letters | 2014 | 6 Pages |
Abstract
Recently, a class of machine learning-inspired procedures, termed kernel machine methods, has been extensively developed in the statistical literature. In this note, we construct a so-called ‘adaptively minimax’ kernel machine. Such a construction highlights the limits on the interpretability of such kernel machines.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Debashis Ghosh,