Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.26/8134
Título: Features selection in Discrete Discriminant Analysis
Autor: Marques, Anabela
Ferreira, Ana Sousa
Cardoso, Margarida
Palavras-chave: Discrete Discriminant Analysis
Combining models
Dependence Trees model
First Order Independence model
Hierarchical Coupling procedure
Variable selection
Data: Jun-2011
Citação: In Book of abstracts of the 14th Applied Stochastic Models and Data Analysis International Conference (ASMDA2011). Rome, 2011
Resumo: In discrete discriminant analysis dimensionality problems occur, particularly when dealing with data from the social sciences, humanities and health. In these domains, one often has to classify entities with a high number of explanatory variables when compared to the number of observations available. In the present work we address the problem of features selection in classification, aiming to identify the variables that most discriminate between the a priori defined classes, reducing the number of parameters to estimate, turning the results easier to interpret and reducing the runtime of the methods used. We specially address classification using a recently methodological approach based on a linear combination of the First-order Independence Model (FOIM) and the Dependence Trees Model (DTM). Data of small and moderate size are considered.
Descrição: Resumo de comunicação em póster apresentada em 14th International Conference on Applied Stochastic Models and Data Analysis (ASMDA2011), Rome, June 7-10 2011
Peer review: yes
URI: http://hdl.handle.net/10400.26/8134
Aparece nas colecções:IPS - ESTB - SMG - Comunicações em congressos

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