[R] Fisher LDA and prior=c(...) argument
Edoardo M Airoldi
eairoldi at stat.cmu.edu
Mon May 19 00:43:38 CEST 2003
hello,
I am using LDA and QDA function of MASS library. I understand Fisher LDA
is a method non-probabilistic in nature, so I wonder what happens when I
try to predict my test set examples as in:
> fit <- lda(labels~., data=train.table, prior=c(.5,.5))
> pred <- predict(fit, data=test.table, prior=c(.5,.5))
Specifically I ask this because in my problem there are 700 examples
class A, and 50 in class B, and I'd be glad to use a way to weight the
contribution of the examples in different classes.
My guess is that the CODE above estimates the likelihood of of the Fisher
scores for (example | class) and then implements the Bayes rule to return
the maximum a-posteriori class.
Is that correct? Any pointer towards that direction is appreciated.
Please cc to edo at stat.cmu.edu your reply.
Thanks
Edoardo M. Airoldi
http://www.stat.cmu.edu/~eairoldi
BH 232L (412) 268.7829
PC Lab (412) 268.8719
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