DISCRIMINANT-ANALYSIS BY GAUSSIAN MIXTURES

Citation
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
ISSN journal
00359246 → ACNP
Volume
58
Issue
1
Year of publication
1996
Pages
155 - 176
Database
ISI
SICI code
1369-7412(1996)58:1<155:DBGM>2.0.ZU;2-N
Abstract
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.