New Discrimination Procedure of Location Model for Handling Large Categorical Variables
The location model proposed in the past is a predictive discriminant rule that can classify new observations into one of two predefined groups based on mixtures of continuous and categorical variables. The ability of location model to discriminate new observation correctly is highly dependent on the...
Main Authors: | Hamid, Hashibah, Long, Mei Mei, Syed Yahaya, Sharipah Soaad |
---|---|
Format: | Article |
Language: | English |
Published: |
Universiti Kebangsaan Malaysia
2017
|
Subjects: | |
Online Access: | https://repo.uum.edu.my/id/eprint/30823/1/SM%2046%2006%202017%201001-1010.pdf http://dx.doi.org/10.17576/jsm-2017-4606-20 |
Similar Items
-
Variables extraction on large binary variables in discriminant analysis based on mixed variables location model
by: Long, Mei Mei, et al.
Published: (2015) -
Multiple correspondence analysis for handling large binary variables in smoothed location model
by: Ngu, Penny Ai Huong, et al.
Published: (2015) -
Performance Analysis and Discrimination Procedure of Two-Group Location Model with Some Continuous and High-Dimensional of Binary Variables
by: Hamid, Hashibah, et al.
Published: (2022) -
Some investigations on the LDA when handling large number of variable
by: Hamid, Hashibah, et al.
Published: (2010) -
A new approach for classifying large number of mixed variables
by: Hamid, Hashibah
Published: (2010)