Robust linear discriminant analysis with automatic trimmed mean
Linear discriminant analysis (LDA) is a multivariate statistical technique used to determine which continuous variables discriminate between two or more naturally occurring groups. This technique creates a linear discriminant function that yields optimal classification rule between two or more group...
Main Authors: | Syed Yahaya, Sharipah Soaad, Lim, Yai-Fung, Ali, Hazlina, Omar, Zurni |
---|---|
Format: | Article |
Language: | English |
Published: |
Universiti Teknikal Malaysia Melaka
2016
|
Subjects: | |
Online Access: | https://repo.uum.edu.my/id/eprint/20520/1/JTEC%208%2010%202016%201%203.pdf |
Similar Items
-
Robust Linear Discriminant Analysis with Highest Breakdown Point Estimator
by: Yai, Fung Lim, et al.
Published: (2018) -
Winsorization on linear discriminant analysis
by: Lim, Yai-Fung, et al.
Published: (2016) -
Robust linear discriminant models to solve financial crisis in banking sectors
by: Lim, Yai-Fung, et al.
Published: (2014) -
A computationally efficient of robust mahalanobis distance based on MVV estimator
by: Ali, Hazlina, et al.
Published: (2015) -
Comparing groups using robust H statistic with adaptive trimmed mean
by: Nur Faraidah Muhammad Di,, et al.
Published: (2014)