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Activity Number: 655
Type: Contributed
Date/Time: Thursday, August 13, 2015 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistical Learning and Data Mining
Abstract #315603
Title: Robust Classification for Functional Data
Author(s): Abhirup Mallik* and Snigdhansu Chatterjee
Companies: University of Minnesota and University of Minnesota
Keywords: classification ; functional ; robust
Abstract:

Functional data classification has many important applications in medicine and chemometrics and various other fields. The data available in this field usually comes preprocessed with various transformations. In many cases details of these pre-processing remains unknown to the statistician. We investigate classification methods for functional data and analyze their performance under various transformations. We propose the use of rank based methods that would be relatively robust under certain class of transformations. We discuss some theoretical properties of such classifiers and demonstrate their performance in simulated and real data sets.


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