[R] how to reconstruct the discriminant funciton from lda$prior, $means and $scaling

[Janet Huang]

Hi R folks,

How can I generate the discriment function from lda? 

I have an unbalanced data set. one class has about 25
entries and another class has about 200 entries. 

I used lda for classification 
> z<- lda(V3 ~ V1+V2, data) 
> z
Prior probabilities of groups:
         0          1 
0.91111111 0.08888889 

Group means:
         V1         V2
0 0.4445161 0.04723951
1 0.4058900 0.06934000

Coefficients of linear discriminants:
         LD1
V1 -30.24734
V2  12.56484

predict(z) only give me 11 errors.

I used the following equations to reconstruct the
discrimiat function: 

>gmean <- z$prior %*% z$means
>const <- as.numeric(gmean %*% z$scaling)
>slope <- -z$scaling[1]/z$scaling[2]
>intercept <- const/z$scaling[2] 
>abline(intercept, slope) 

however, this line gives about 50 errors, not the same
one used by the predict(z).

Any suggestions? 

Thanks. 
Janet