J. L. Vicente Villardón

Classical Biplot methods allow for the simultaneous representation of individuals and continuous variables in a given data matrix. When variables are binary, categorical or ordinal, a classical linear biplot representation is not suitable. We propose a linear biplot representation based on logistic response models. The coordinates of individuals and variables are computed to have logistic responses along the biplot dimensions. The method is related to logistic regression in the same way that Classical Biplot Analysis (CBA) is related to linear regression. Thus we refer to the method as Logistic Biplot (LB). In the same way as Linear Biplots are related to Principal Components Analysis, Logistic Biplots are related to Latent Trait Analysis or Item Response Theory. The geometry of those kinds of biplots is studied and their usefulness in Data Mining is illustrated using data on SNPs (Single Nucleotide Polymorphisms) from the HAPMAP project.

Palabras clave: logistic biplot, categorical data, regression biplots

URL de la comunicación: http://biplot.usal.es/ClassicalBiplot/index.html

Fichero de la comunicación:

Programado

JC3 Clasificación y análisis multivariante 2
19 de abril de 2012  12:00
Sala Londres

Biplots with correlations that are linear in the angle

J. Graffelman

Aplicación a catálogos estelares de técnicas estadísticas de reducción de la dimensión y clasificación

A. Berihuete, A. Jimenez Jimenez, F. Álvarez González

Detección de interacciones relevantes para el problema de clasificación binaria en conjuntos de datos de alta dimensión

J. Martín Arevalillo, H. Navarro Veguillas