[R] Prediction in discriminant analysis

[Joris Meys]

You use the function "predict" for that. You give a data frame with
the new observations, and make sure the variables have exactly the
same name.

# run example
library(MASS)
Class <- as.factor(rep(c("A","B","C"),each=30))

X1 <- c(rnorm(30),rnorm(30,3,2),rnorm(30,-3,1))
X2 <- c(rnorm(30,5,3),rnorm(30,-2,4),rnorm(30,2,2))

result <- lda(Class~X1+X2)

newdat <- data.frame(X1=rnorm(10),X2=rnorm(10,5,3))

predictions <- predict(result,newdat)  #
predictions$class   # gives the class to which the new observation belongs
predictions$posterior # gives the posterior probabilities for each
observation and for all classes
# end example

Cheers
Joris


On Sat, Jun 5, 2010 at 6:37 AM, suman dhara <suman.dhara89 at gmail.com> wrote:
> Sir,
> I am working with multiclass discriminant analysis.(say response variable
> has 3classes).In R, using lda(), I get 2 sets of coefficients for the
> discriminant function.Now, I want to put a new x-vector(vector of
> independent variables) and want to check it corresponds to which class of
> y.Is there any formula for doing this? or how can I do this?
>
>
>
> Regards,
> Suman Dhara
>
>        [[alternative HTML version deleted]]
>
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Ghent University
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