A carregar...
Publicação
Combining models in discrete discriminant analysis in the multiclass case
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 52.88 KB | Adobe PDF |
Orientador(es)
Resumo(s)
The idea of combining models in Discrete Discriminant Analysis (DDA) is present in a growing number of papers which aim to obtain more robust and more stable models than any of the competing ones. This seems to be a promising approach since it is known that different DDA models perform differently on different subjects (Brito et al.(2006)). In particular, this will be a more relevant issue if the groups are not well separated, which often occurs in practice.
In the present work a new methodological approach is suggested which is based on DDA models' combination. The multiclass problem is decomposed into several dichotomous problems that are nested in a hierarchical binary tree (Sousa Ferreira (2000), Brito et al. (2006)) and at each level of the binary tree a new combining model is proposed to derive the decision rule. This combining model is based on two well known models in the literature - the First-order Independence Model (FOIM) and the Dependence Trees Model (DTM) (Celeux and Nakache (1994)).
The MATLAB software is used for the algorithms' implementation and the proposed
approach is illustrated in a DDA application.
Descrição
Resumo de comunicação oral em póster apresentado em COMPSTAT2008 - 18th International Conference on Computational Statistics, Porto, Portugal, 24 a 29 de Agosto 2008
Palavras-chave
Combining model Discrete discriminant analysis First-order independence model Dependence trees model
Contexto Educativo
Citação
In COMPSTAST'2008: Book of abstracts. (2008). Porto: FEP
Editora
Faculdade de Economia da Universidade do Porto