Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/22653
Authors: 
Czogiel, Irina
Luebke, Karsten
Zentgraf, Marc
Weihs, Claus
Year of Publication: 
2006
Series/Report no.: 
Technical Report / Universität Dortmund, SFB 475 Komplexitätsreduktion in Multivariaten Datenstrukturen 2006,10
Abstract: 
Despite its age, the Linear Discriminant Analysis performs well even in situations where the underlying premises like normally distributed data with constant covariance matrices over all classes are not met. It is, however, a global technique that does not regard the nature of an individual observation to be classified. By weighting each training observation according to its distance to the observation of interest, a global classifier can be transformed into an observation specific approach. So far, this has been done for logistic discrimination. By using LDA instead, the computation of the local classifier is much simpler. Moreover, it is ready for applications in multi-class situations.
Subjects: 
classification
local models
LDA
Document Type: 
Working Paper

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