A robust method of selecting variables with the greatest discriminatory power is presented in the paper. It is based on the robustified Wilks A statistic and can be applied in a multi-group discrimination problem. An application to some respiratory disease data together with a comparison of the clas
Robust selection of variables in linear discriminant analysis
โ Scribed by Valentin Todorov
- Publisher
- Springer
- Year
- 2007
- Tongue
- English
- Weight
- 352 KB
- Volume
- 15
- Category
- Article
- ISSN
- 1613-981X
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
A problem frequently encountered by the practitioner in Discriminant Analysis is how to select the best variables. In mixed discriminant analysis (MDA), i.e., discriminant analysis with both continuous and discrete variables, the problem is more di cult because of the di erent nature of the variable
Linear discriminant analysis (LDA) is an effective tool in multivariate multigroup data analysis. A standard technique for LDA is to project the data from a high-dimensional space onto a perceivable subspace such that the data can be separated by visual inspection. The criterion of LDA, unfortunatel