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
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