Seminar 2023-25-08

Real-time Discriminant Analysis in the Presence of Label and Measurement Noise

Mia Hubert

Professor

Department of Mathematics, section of Statistics and Data Science

KU Leuven

Date: Friday, August 25, 2023

Time: 11:00 A.M. – 12:00 P.M. Eastern Time

Location: Johnson Center, Room 325 Meeting Room A

Quadratic discriminant analysis (QDA) is a widely used classification technique. Based on a training dataset, each class in the data is characterized by an estimate of its center and shape, which can then be used to assign unseen observations to one of the classes. The traditional QDA rule relies on the empirical mean and covariance matrix. Unfortunately, these estimators are sensitive to label and measurement noise which often impairs the model's predictive ability. Robust estimators of location and scatter are resistant to this type of contamination. However, they have a prohibitive computational cost for large scale industrial experiments. First, we present a novel QDA method based on a real-time robust algorithm. Secondly, we introduce the classmap, a graphical display to visualize aspects of the classification results and to identify label and measurement noise.

Mia Hubert is professor at the KU Leuven, department of Mathematics, section of Statistics and Data Science. Her research focuses on robust statistics, outlier detection, data visualization, depth functions, and the development of statistical software. She is an elected fellow of the ISI and has served as associate editor for several journals such as JCGS, CSDA, and Technometrics. She is co-founder and organizer of The Rousseeuw Prize for Statistics, a new biennial prize which awards pioneering work in statistical methodology.

Nicholas Rios