Sesssion 9 : Transformation Discriminant Analysis
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
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.