Statistics and Data Science Seminar
Prof. Junhui Wang
UIC, MSCS
Probability Estimation for Large Margin Classifiers
Abstract: Large margin classifiers have proven to be effective in delivering
high predictive accuracy, particularly those focusing on the
decision boundaries and bypassing the requirement of estimating the
class probability given input for discrimination. As a result, these
classifiers may not directly yield an estimated class probability,
which is of interest itself in many real applications. In this talk,
I will present a novel method to estimate the class probability
through sequential weighted classifications, by utilizing features
of interval estimation of large margin classifiers. In particular, I
will discuss four aspects: (1) the idea and methodology development;
(2) tuning parameter selection; (3) regularization solution path;
(4) a statistical learning theory. Numerical examples will be
provided to demonstrate the advantage of our proposed methodology.
Wednesday October 8, 2008 at 4:15 PM in SEO 612