Name
Title | ||
|---|---|---|
LDA pre-processing for classification: class-dependent single objective GA and multi-objective GA approaches |
Abstract | ||
|---|---|---|
Pre-processing of classification data can be helpful regardless of the type of classifier. The objective of this pre-processing step is to achieve a high degree of separation among classes before the classifier is trained or tested. This results into a trace ratio problem which is difficult to solve. Methods such as Linear Discriminant Analysis (LDA) have already been used for the solution of this problem by turning it into a simpler yet inexact problem. Also, in classical LDA, the covariances of different classes are assumed to be similar, which is not the case in real-world problems. In this paper, a class-dependent approach to finding the linear transformation is proposed. This method solves the trace ratio problem directly and also removes the requirement of similar covariance matrices. While giving good results, the method is computationally expensive. To reduce the computational cost while maintaining the benefits of the class-dependent method, a multi-objective formulation is proposed and solved using NSGA-II. Simulation results show great improvement in classification using various classifiers. |
Year | Venue | Keywords |
|---|---|---|
2009 | IDEAL | linear discriminant analysis,inexact problem,trace ratio problem,class-dependent approach,class-dependent method,multi-objective ga approach,class-dependent single objective,various classifier,classical lda,similar covariance matrix,real-world problem,lda pre-processing,classification data,linear transformation,genetic algorithm,classification |
Field | DocType | Volume |
Six degrees of separation,Pattern recognition,Matrix (mathematics),Computer science,Artificial intelligence,Linear map,Linear discriminant analysis,Classifier (linguistics),Single objective,Machine learning,Genetic algorithm,Covariance | Conference | 5788 |
ISSN | ISBN | Citations |
0302-9743 | 3-642-04393-3 | 0 |
PageRank | References | Authors |
0.34 | 5 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Modjtaba Khalidji | 1 | 1 | 0.70 |
| Hossein Moeinzadeh | 2 | 23 | 4.07 |
| Ahmad Akbari | 3 | 159 | 23.17 |
| Bijan Raahemi | 4 | 155 | 22.29 |