Sesssion 9 : Transformation Discriminant Analysis

Presenter Information/ Coauthors Information

Yana Melnykov, University of Alabama - TuscaloosaFollow

Presentation Type

Invited

Student

No

Track

Methodology

Abstract

Multigroup discriminant analysis is a key classification technique with diverse applications. Linear and quadratic discriminant analysis (LDA and QDA) are popular methods that assume normal class distributions. This limits their application to non-normal data. We propose a transformation-based extension of LDA and QDA to handle asymmetry and skewness. Simulations and real-world applications show our method outperforms existing approaches in various scenarios.

Start Date

2-7-2025 2:30 PM

End Date

2-7-2025 3:30 PM

This document is currently not available here.

Share

COinS
 
Feb 7th, 2:30 PM Feb 7th, 3:30 PM

Sesssion 9 : Transformation Discriminant Analysis

Pasque (Room 255)

Multigroup discriminant analysis is a key classification technique with diverse applications. Linear and quadratic discriminant analysis (LDA and QDA) are popular methods that assume normal class distributions. This limits their application to non-normal data. We propose a transformation-based extension of LDA and QDA to handle asymmetry and skewness. Simulations and real-world applications show our method outperforms existing approaches in various scenarios.