R help - Mar 2007 - Jackknife estimates of predict.lda success rate

Dear all

I have used the lda and predict functions to classify a set of objects
of unknown origin. I would like to use a jackknife reclassification to
assess the degree to which the outcomes deviate from that expected by
chance. However, I can't find any function that allows me to do this.
Any suggestions of how to generate the jackknife reclassification to
assess classification accuracy? (BTW, commands I used to generate
predictions appended below.)

Many thanks

Mat Vanderklift
> library(MASS)
> Sep04 <- read.table("Sep04 dataframe2.txt", header=TRUE)
> trainSep04 <- Sep04[1:125,]
> Sep04.lda <- lda(Reef ~ ., trainSep04)
> Sep04.lda
> predict.Sep04 <- predict(Sep04.lda, Sep04) $class
 


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Dear all
I have used the lda and predict functions to classify a set of objects of
unknown origin. I would like to use a jackknife reclassification to assess the
degree to which the outcomes deviate from that expected by chance. However, I
can't find any function that allows me to do this. Any suggestions of how to
generate the jackknife reclassification to assess classification accuracy? (BTW,
commands I used to generate predictions appended below.)
Many thanks
Mat Vanderklift
> library(MASS)
> Sep04 <- read.table("Sep04 dataframe2.txt", header=TRUE)
> trainSep04 <- Sep04[1:125,]
> Sep04.lda <- lda(Reef ~ ., trainSep04)
> Sep04.lda
> predict.Sep04 <- predict(Sep04.lda, Sep04) $class
?