T. Hastie et R. Tibshirani, DISCRIMINANT-ANALYSIS BY GAUSSIAN MIXTURES, Journal of the Royal Statistical Society. Series B: Methodological, 58(1), 1996, pp. 155-176
Citations number
22
Categorie Soggetti
Statistic & Probability","Statistic & Probability
Journal title
Journal of the Royal Statistical Society. Series B: Methodological
Fisher-Rao linear discriminant analysis (LDA) is a valuable tool for m
ultigroup classification. LDA is equivalent to maximum likelihood clas
sification assuming Gaussian distributions for each class. In this pap
er, we fit Gaussian mixtures to each class to facilitate effective cla
ssification in non-normal settings, especially when the classes are cl
ustered. Low dimensional views are an important by-product of LDA - ou
r new techniques inherit this feature. We can control the within-class
spread of the subclass centres relative to the between-class spread.
Our technique for fitting these models permits a natural blend with no
nparametric versions of LDA.