
  
Dear colleagues,

I run discriminant analysis on a dataset with plants species presence as  variables (binary, independent) and lakes # as cases. I also have a classification variable with 4 classes (representing each PC of PCA of the same matrix, but transposed). 

I have some problems with interpreting Fisher's classification function coefficients. 
It is said that a case belongs to the class for which the score is highest. In all books you can find something about this, one compares (e.g.) score= 0.1 with score= 2.5 (of which 2.5 is largest).

My question is: would an object belong to a class with score=0.1 or to one with the score= -75 ?. I don´t know if I should take that state literary.

Any suggestion much appreciated.

Thanks

Dragos Zaharescu
@VigoUni.


      
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