Department of Statistics Seminar
North Carolina State University
Presents
Susan Murphy
University of Michigan
A Prediction Interval for the Misclassification Rate
Abstract
The misclassification rate of a classifier is a non-smooth functions of the
classifier. The estimated rate suffers from bias due to over-fitting and the
misclassification rate is a “minimized" quantity. For both of these reasons the
construction of measures of confidence such as estimates of variance and
confidence/prediction intervals are challenging. We discuss this problem and
propose a method based on the use of a smooth upper bound combined with the
bootstrap.
This upper bound utilizes the surrogate loss that is used in the
construction of the classifier.
Friday, October 31 2008
3:35 - 5:00 pm
321 Riddick Hall
Refreshments will be served in the common area of Riddick at 3:00 pm.
NOTE: No food or drink is allowed in any of the classrooms in Riddick Hall.